Which ChatGPT Model is Best for You? GPT-5.3-Codex, GPT-5.3-Codex-Spark, GPT-5.2, GPT-5.1, GPT-5, 4.1, 4-o, o-Series

Updated on July 17, 2026

Quick answer: As of July 2026, OpenAI’s current flagship is GPT-5.6 Sol, released July 9, 2026, alongside GPT-5.6 Terra and GPT-5.6 Luna. Inside standard ChatGPT, GPT-5.5 Instant remains the default for everyday chat, and eligible paid plans can reach GPT-5.6 Sol through reasoning settings.

When you’ve been using AI models for as long as the team at Kommunicate, you start building an intuition about which model you use for which purpose.

We make these decisions daily, using OpenAI’s ChatGPT models for writing, coding, customer service, and more. And we’re not alone, around 400-800M users log into ChatGPT every week for their work.

So, which model should you use?

We can answer this by starting from the newest models and moving backward. This makes the lineage easier to understand.

At a high level, OpenAI’s model evolution has moved through four overlapping arcs:

1. Unified Models (GPT-5.3 Codex, GPT-5.2, GPT-5.1, GPT-5 era): These models combine knowledge, deliberate reasoning, and native multimodality in one adaptive system, with automatic routing between “fast” answers and “think-hard” answers. The GPT-5.3 Codex line goes further, specializing in long-horizon agentic software engineering. This arc has since extended further, through GPT-5.4, GPT-5.5, and now GPT-5.6.
2. Bifurcation (the “o” series vs. GPT-4.x): These are specialized reasoning models that spend extra compute at inference time, alongside knowledge/interaction models that scale context, coding, and usability.
3. Alignment & Multimodality (GPT-3.5 → GPT-4/4o): These models were created to follow instructions safely. GPT 4-o added to this with native multimodal capabilities. Voice has since split off into its own dedicated line with GPT-Live-1.
4. Scaling (GPT-1 → GPT-3): The first GPT models were built on massive pre-training data that allowed them to generate and reason while providing answers. 

We will take you through each generation’s capabilities to make this choice easier. We’ll be covering-

1. ChatGPT Models Compared: Which Model Is Most Capable?

2. Which ChatGPT Model Is Best?

3. Cost Comparison Across Different ChatGPT Models

4. ChatGPT Models Explained 

5. Which OpenAI Model Should You Use?

6. Frequently Asked Questions

7. Conclusion

ChatGPT Models Compared: Which Model Is Most Capable?

TL;DR

• GPT-5.6 Sol is now OpenAI’s flagship model (released July 9, 2026), built for frontier reasoning and long-horizon agentic work, alongside two lighter siblings, GPT-5.6 Terra and GPT-5.6 Luna.
• GPT-5.5 is the current default model inside standard ChatGPT, after GPT-5.2 was retired on June 12, 2026.
• GPT-5.3-Codex is the most capable agentic coding model to date, combining frontier coding performance with the reasoning of GPT-5.2 in one model that is also 25% faster.
• GPT-5.3-Codex-Spark is a smaller, ultra-fast variant of GPT-5.3-Codex running on Cerebras hardware, delivering over 1,000 tokens/second for real-time coding.
• GPT-5.2 has been retired from ChatGPT. If you were defaulting to it, you’re already on GPT-5.5.
• GPT-5.1 is still excellent with improved conversational tone and enhanced personalization. It has also been retired from ChatGPT as of March 11, 2026.
• For live, human-like voice/vision interaction, use GPT-Live-1 (voice) or GPT-4o (vision + text). GPT-Live replaced Advanced Voice Mode on July 8, 2026.
  • For extremely long-context jobs (like large codebases), GPT-4.1 offers up to 1M tokens.
  • The o-series (o3/o1/o4-mini) are still excellent when you want explicit, tunable “reasoning effort.”

GPT Versions Ranked

Status	Model family (release)	Core Aim	Reasoning/Math	Coding	Multimodality	Typical strengths
🆕	GPT-5.6 Sol (Jul 2026)	New flagship for frontier reasoning and long-horizon agentic work	Elite	Elite	Text + vision	Hardest reasoning, research, long-running agent tasks
🆕	GPT-5.6 Terra (Jul 2026)	Balanced everyday model, GPT-5.5-competitive at lower cost	Strong	Strong	Text + vision	Production workloads needing solid reasoning without flagship pricing
🆕	GPT-5.6 Luna (Jul 2026)	Fast, cost-sensitive workloads	Good	Good	Text + vision	High-throughput tasks like ticket triage
🆕	GPT-Live-1 / GPT-Live-1 mini (Jul 2026)	Full-duplex voice, listens and speaks simultaneously	N/A	N/A	Voice	Live, spoken interaction, replaces Advanced Voice Mode
🆕	GPT-5.5 (Jun 2026)	Current default unified model in ChatGPT (Instant/Thinking/Pro)	Elite	Elite	Text + vision	Default choice for most everyday use
🆕	GPT-5.4 / GPT-5.4 mini (Spring 2026)	Unifies reasoning, coding, and agentic work, folds in GPT-5.3-Codex’s coding strength	Elite	Elite	Text + vision	Office-heavy work (sheets, slides, docs) needing real reasoning
	GPT-5.3-Codex (Feb 2026)	Most capable agentic coding model; combines frontier coding + 5.2 reasoning; 25% faster than GPT-5.2-Codex	Elite	Elite (best in class agentic software engineering)	Text + Vision (Image in, text out)	Long horizon software tasks, multi-file refactors, research + tool use, real world dev work
	GPT-5.3-Codex-Spark (Feb 2026)	Smaller, ultra-fast real-time coding model; first OpenAI model on non-Nvidia hardware (Cerebras WSE-3)	Strong	Strong (1,000+ tokens/sec; SWE-Bench Pro parity with full model)	Text only	Real-time coding, rapid iteration, hands-on coding sessions, beginner-friendly AI pair programming
✏️	GPT-5.2 (Dec 2025, retired from ChatGPT Jun 12, 2026)	Latest unified flagship; strongest instruction following + agentic reliability	Elite (improved adaptive reasoning; Instant / Thinking / Pro tiers)	Elite (best-in-class agentic coding + tool use)	Text + vision (image in, text out)	Best general default; multi-step execution, complex workflows, knowledge work
✏️	GPT-5.1 (Nov 2025, retired from ChatGPT Mar 11, 2026)	Refined unified model (tone + personalization + configurable reasoning effort)	Elite (Instant vs Thinking; configurable reasoning)	Elite (instruction following + tool use)	Text + vision	“Most refined UX” among GPT-5.x; strong default when you want 5.x but slightly lower cost than 5.2
	GPT-5 (Aug 2025)	First “thinking built in” unified GPT-5 baseline	Elite (auto-routes to deeper thinking)	Elite (strong agentic coding)	Text + vision	Still a strong all-around model; broadly capable across knowledge + tools + vision
	o-series (o3 / o1 / o4-mini, 2024–25)	Deliberate, tunable inference-time reasoning	Elite (explicit “reasoning effort”)	Strong–Elite (STEM-heavy)	Text (+ image input on supported o-models)	Hard math/logic; competitive programming; research workflows where you want explicit “think more” control
	GPT-4o (May 2024)	Real-time omni interaction; fast multimodal UX	Strong	Strong	Text + vision (audio via dedicated 4o Audio/Realtime models)	Live voice experiences, low-latency multimodal interactions, general-purpose assistant tasks
	GPT-4.1 (Apr 2025)	Long-context + strong instruction following/tool calling	Strong	Strong–Elite	Text + vision	Massive-context analysis (codebases, multi-doc); strong tool calling without a separate “reasoning” step
✏️	GPT-4.5 (Feb 2025, retired from ChatGPT Jun 26, 2026)	Scaled unsupervised “EQ” & fluency (research preview)	Strong (not a reasoning-first model)	Strong	Text + vision	Natural conversation, writing/coaching, creative ideation; superseded for most dev use cases by 4.1 on cost/perf
	GPT-4 / 4-Turbo (2023)	High-intelligence GPT generation; early flagship w/ vision	Strong	Strong	Text + vision	High-reliability enterprise tasks; stable legacy option
	GPT-3.5 (2022)	RLHF/Instruction-following for chat	Moderate–Strong	Moderate–Strong	Text	“Classic” cheaper chat model; legacy compatibility
	GPT-3 (2020)	Few-shot / in-context learning at scale	Moderate	Moderate	Text	Breakthrough generalist few-shot behavior; foundation for API-era LLM apps
	GPT-2 (2019)	Zero-shot generalization; staged release	Basic–Moderate	Basic	Text	Coherent long-form generation; catalyzed safety debate around release
	GPT-1 (2018)	Generative pre-training + supervised fine-tuning	Basic	Basic	Text	Academic proof-of-concept; established pre-train → fine-tune paradigm

Which ChatGPT Model Is Best?

There’s no single “best” ChatGPT model, the right one depends on the task. Three defaults cover most people:

• Long-running agentic software engineering: GPT-5.3-Codex or GPT-5.4.
• Everyday chat, writing, general questions: GPT-5.5 Instant, still the ChatGPT default.
• Hard reasoning, research, high-stakes accuracy: GPT-5.6 Sol if your plan includes it, or GPT-5.5 Thinking otherwise.

The Best ChatGPT Model For Your Use-Case

1. For the Hardest Reasoning and Long-Running Agent Work, use GPT-5.6 Sol – OpenAI’s newest flagship, released July 9, 2026, reachable via reasoning settings on eligible paid plans. Kommunicate customers can already run comparable reasoning-tier models for AI agents without managing a separate API key.
2. For Agentic Coding & Professional Software Engineering, use GPT-5.3-Codex – the most capable coding model to date, combining advanced reasoning with state-of-the-art software engineering performance on real-world benchmarks.
3. For Real-Time Coding Collaboration, use GPT-5.3-Codex-Spark – designed for instant, interactive coding with 1,000+ tokens/second output. Best for rapid prototyping, targeted edits, and hands-on iteration.
4. For Most General Use Cases, use GPT-5.5 – the current ChatGPT default, after GPT-5.2 was retired in June 2026. You can already deploy GPT-5.5 directly inside Kommunicate via the OpenAI integration, no separate API key required.
5. For Deliberate, Controllable Reasoning, use the o-series (o3, o1, o4-mini) – gives explicit control over “reasoning effort” and excels on STEM logic.
6. For Long-Context Work (Codebases, Multiple Documents), use GPT-4.1 – with 1 million tokens in context.
7. For Live, Human-Like Multimodal UX (Voice/Vision), use GPT-4o – native speech pipeline with ~232-320 ms audio latency. For voice specifically, see GPT-Live-1 below, which has replaced this role.
8. For Budget/High-Volume Conversational AI, use GPT-3.5 Turbo – lower cost for basic chat interfaces. See our ChatGPT-4 vs ChatGPT-3.5 comparison for a deeper breakdown of when 3.5 is still the right call.
9. For Live, Spoken Conversation, use GPT-Live-1 (or GPT-Live-1 mini) – OpenAI’s dedicated full-duplex voice models, which replaced Advanced Voice Mode as of July 8, 2026. This is now the better answer than GPT-4o for anything voice-first. If you’re evaluating a live voice experience for your own support stack, see what AI voice agents need operationally, or explore Kommunicate’s Voice AI product directly.

While OpenAI keeps adding newer models which are safe and faster, they keep retiring older models. The primary models retired from ChatGPT include:

• GPT-4.5 (retired June 26, 2026, including custom GPTs, existing chats rolled to GPT-5.5)
• GPT-5.2 (all variants, retired June 12, 2026, rolled to GPT-5.5)
• GPT-5.1 (all variants, retired March 11, 2026, rolled to GPT-5.3 Instant, GPT-5.4 Thinking, or GPT-5.4 Pro)

• GPT-5 (Instant and Thinking variants)
• GPT-4o
• GPT-4.1
• GPT-4.1 mini
• OpenAI o4-mini

Here’s a quick run-down of the best model for each use case:

Status	Model	Context length	Good for
🆕	GPT-5.6 Sol	1,050,000 tokens	Frontier reasoning, long-horizon agentic work, hardest tasks
🆕	GPT-5.6 Terra	1,050,000 tokens	Balanced everyday production work at lower cost
🆕	GPT-5.6 Luna	1,050,000 tokens	High-throughput, cost-sensitive tasks
🆕	GPT-Live-1 / mini	N/A (voice)	Live, full-duplex spoken conversation
🆕	GPT-5.5	400,000 tokens	Current ChatGPT default; general chat, reasoning, tool use
🆕	GPT-5.4 / mini	400,000 tokens	Reasoning + coding + office work (sheets, slides, docs) in one model
	GPT-5.3-Codex	400,000 tokens	Best for serious, long-horizon agentic software engineering tasks.
	GPT-5.3-Codex-Spark	128,000 tokens	Best for real-time, interactive coding collaboration where instant responses matter.
⚠️	GPT-5.2 Instant (retired Jun 12, 2026)	400,000 tokens	Fast, conversational responses; general chat; brainstorming; strong instruction following with speed
⚠️	GPT-5.2 Thinking (retired Jun 12, 2026)	400,000 tokens	Complex reasoning; multi-step planning; mathematical problems; higher reliability on hard tasks
⚠️	GPT-5.1 Instant (retired Mar 11, 2026)	400,000 tokens	Fast, conversational responses; general chat; brainstorming; customizable tone
⚠️	GPT-5.1 Thinking (retired Mar 11, 2026)	400,000 tokens	Complex reasoning; multi-step planning; mathematical problems; adaptive computation
	GPT-5	400,000 tokens	Unified knowledge + reasoning; long docs; complex agent/tool workflows
	o3	200,000 tokens	Deep multi-step reasoning; STEM & competitive coding; tunable “think more” effort
	o1	200,000 tokens	“Think-before-answering” reasoning, analysis, and planning for hard problems
	o4-mini	200,000 tokens	Fast, cost-efficient reasoning; coding & visual tasks at lower cost
	GPT-4.1	~1,000,000 tokens	Massive long-context work (codebases, multi-doc legal); strong instruction following
	GPT-4 Turbo	128,000 tokens	Long documents and chats with GPT-4-level quality at lower cost
✏️	GPT-4o (voice role now superseded by GPT-Live-1, see above)	128,000 tokens	Real-time multimodal (voice/vision) interaction with low latency
	GPT-3.5 Turbo	16,385 tokens	Budget conversational AI and aligned instruction following

Now that we have a basic idea of what tasks each model can perform, let’s look at the pricing. 

Also Read:

1. 11 AI Tools For Customer Support Teams
2. 10 Best WhatsApp AI Chatbots

GPT-5.3-Codex vs GPT-5.3-Codex-Spark vs GPT-5.2 vs GPT 5.1 vs o-series vs. GPT-4.1/4.5 vs. GPT-4/4o vs. GPT-3.5 Turbo. Cost Comparison

After the DeepSeek release, OpenAI has been laser-focused on creating cheaper models. Their new models, like GPT-5 offer improved performance at a lower cost. Let’s take a look:

Status	Family	Model (SKU)	Input $/1M	Cached input $/1M	Output $/1M	Realtime (text) $/1M In/Out
🆕	GPT-5.6	gpt-5.6-sol	5	TBD	30	N/A
🆕	GPT-5.6	gpt-5.6-terra	2.5	TBD	15	N/A
🆕	GPT-5.6	gpt-5.6-luna	1	TBD	6	N/A
🆕	GPT-5.5	gpt-5.5 (all variants)	TBD, confirm on OpenAI pricing page	TBD	TBD	N/A
🆕	GPT-5.4	gpt-5.4 / gpt-5.4-mini	TBD, confirm on OpenAI pricing page	TBD	TBD	N/A
	GPT-5.3-Codex	gpt-5.3-codex	TBD	TBD	TBD	N/A
	GPT-5.3-Codex-Spark	Research preview (ChatGPT Pro only)	Not yet publicly priced	–	–	–
⚠️	GPT-5.2 (retired Jun 12, 2026, kept for legacy API reference)	gpt-5.2-chat-latest	1.75	0.175	14	N/A
⚠️	GPT-5.2 (retired Jun 12, 2026, kept for legacy API reference)	gpt-5.2	1.75	0.175	14	N/A
⚠️	GPT-5.2 (retired Jun 12, 2026, kept for legacy API reference)	gpt-5.2-pro	21	—	168	N/A
⚠️	GPT-5.1 (retired Mar 11, 2026, kept for legacy API reference)	gpt-5.1-chat-latest	1.25	0.125	10	N/A
	GPT-5	gpt-5	1.25	0.125	10	N/A
	GPT-5	gpt-5-mini	0.25	0.025	2	N/A
	GPT-5	gpt-5-nano	0.05	0.005	0.4	N/A
	o-series (reasoning)	o3	2	0.5	8	N/A
	o-series (reasoning)	o3-pro	20	—	80	N/A
	o-series (reasoning)	o1	15	7.5	60	N/A
	o-series (reasoning)	o4-mini	1.1	0.275	4.4	N/A
	GPT-4.1 / 4.5	gpt-4.1	2	0.5	8	N/A
✏️	GPT-4.1 / 4.5	GPT-4.5 (retired from ChatGPT Jun 26, 2026, preview pricing kept for accuracy)	75	37.50*	150	N/A
	GPT-4 / 4o	GPT-4 (8k)	30	—	60	N/A
	GPT-4 / 4o	GPT-4 Turbo (128k)	10	—	30	N/A
	GPT-4 / 4o	GPT-4o (2024-11-20 snapshot)	2.5	1.25	10	5.00 / 20.00 (gpt-4o-realtime-preview)
	GPT-4 / 4o	GPT-4o mini	0.15	0.075	0.6	0.60 / 2.40 (gpt-4o-mini-realtime-preview)
	GPT-3.5	GPT-3.5-turbo-0125	0.5	—	1.5	N/A

Notes on Pricing

• GPT-5.6 Sol/Terra/Luna pricing reflects standard short-context rates as of July 2026. Long-context requests cost more.
• GPT-5.2 was retired from ChatGPT on June 12, 2026, the pricing above remains accurate for legacy API usage, but new builds should default to GPT-5.5 or GPT-5.6.
• GPT-5.5 and GPT-5.4 API pricing is marked TBD pending confirmation on OpenAI’s live pricing page. Do not publish invented figures here.

• GPT-5.3-Codex API pricing has not yet been officially announced. GPT-5.3-Codex-Spark is currently available as a research preview to ChatGPT Pro subscribers ($200/mo) only and is not available via the API.
• GPT-5.2 is priced above GPT-5/5.1, with deeper cache discounts. GPT-5.2 is $1.75 / 1M input and $14 / 1M output, and cached input is $0.175 / 1M (a 90% discount vs standard input). OpenAI also notes that despite higher per-token pricing, GPT-5.2 can be cost-effective due to improved token efficiency on agentic work.
• GPT-5.1 maintains the same pricing as GPT-5 while offering improved performance and user experience
• The GPT-4.5 Preview has been discontinued, but we’ve included the pricing for accuracy.
• GPT-4o is the model used for real-time voice conversations, so we’ve included the real-time API pricing.
• For repeated prompts, prompt-caching can cut prompt costs by ~75% on GPT 4.1.

Now that you know the GPT models’ pricing, let’s talk about each model in turn. 

ChatGPT Models Explained – GPT-5.3-Codex vs GPT-5.3-Codex-Spark vs GPT 5.2 vs GPT-5.1 vs GPT-5 vs GPT 4.1 vs GPT 4-0 vs o-Series vs GPT-3.5 Turbo.

Let’s understand each model’s individual structures, capabilities, and use cases under the ChatGPT umbrella.

GPT-5.6 Sol – OpenAI’s New Flagship for Frontier Reasoning

What it is: Released July 9, 2026, GPT-5.6 Sol is OpenAI’s flagship model, built for frontier reasoning and long-horizon agentic work. It introduces a new “ultra” reasoning mode that lets the system work harder on a task and delegate pieces of it to submodels. Third-party benchmarking shows it setting a new high on the Artificial Analysis Coding Agent Index, and OpenAI reports roughly 54% better token efficiency on agentic coding tasks compared to its predecessor.

When to use it

• The hardest reasoning, research, and long-running agent work where correctness matters more than speed or cost.
• Complex multi-step planning that needs to stay coherent over a long session.

Strengths

• Leading performance on long-horizon, professional-workflow benchmarks like Agents’ Last Exam.
• Noticeably more token-efficient than its predecessor on agentic coding tasks.
• 1.05M-token context window, among the largest in OpenAI’s current lineup.

Watch Out For

• It isn’t the ChatGPT default. You reach it through reasoning settings on eligible paid plans, not automatically.
• Higher cost per token than Terra or Luna, reserve it for tasks that actually need the extra reasoning depth.

GPT-5.6 Terra – Balanced, Everyday Reasoning at Lower Cost

What it is: Terra is the balanced sibling in the GPT-5.6 family, positioned as roughly GPT-5.5-competitive on performance at a lower price point. It isn’t available in the standard ChatGPT model picker, but you can reach it through ChatGPT Work, Codex, or the API.

When to use it

• Production workloads that need solid reasoning without paying flagship pricing.
• Everyday agentic tasks (drafting, summarizing, moderate multi-step planning) at scale.

Strengths

• Strong reasoning and coding performance close to GPT-5.5, at roughly half the input cost and half the output cost of Sol.
• Same 1.05M-token context window as Sol and Luna.

Watch Out For

• Not accessible through the standard ChatGPT app, only via Work, Codex, or direct API access.
• For genuinely hard reasoning tasks, Sol still outperforms it, Terra trades some ceiling for cost efficiency.

GPT-5.6 Luna – Fast and Cost-Sensitive

What it is: Luna is the fastest, most cost-sensitive model in the GPT-5.6 family, aimed at high-volume workloads where latency and price matter more than squeezing out the last point of benchmark performance.

When to use it

• High-throughput applications, like triaging large support ticket queues or bulk classification, where speed and unit cost outweigh raw reasoning depth.
• Any workload where you’re calling the model thousands of times a day and cost per call compounds quickly.

Strengths

• Lowest cost in the GPT-5.6 family, roughly a fifth of Sol’s input price.
• Same 1.05M-token context window as its siblings, so it isn’t compromised on context length, only on reasoning ceiling and speed trade-offs.

Watch Out For

Like Terra, it’s not in the standard ChatGPT model picker, API/Work/Codex access only.

Not the pick for hard reasoning or long-horizon agentic work, that’s Sol’s job.

GPT-5.5 – The Current ChatGPT Default

What it is: GPT-5.5 replaced GPT-5.2 as the default ChatGPT experience after GPT-5.2 was retired on June 12, 2026. It keeps the same coordinated-variant structure: Instant for fast answers, Thinking for deeper reasoning, and Pro for the highest-stakes work, plus a new GPT-5.5 Instant Mini fallback model for users who hit rate limits.

When to use it

• The default choice if you’re not sure which model to pick.

GPT-5.4 – Reasoning, Coding, and Office Work in One Model

What it is: GPT-5.4 unifies reasoning, coding, and agentic workflows into a single model, and specifically folds in GPT-5.3-Codex’s coding capabilities while improving how the model handles spreadsheets, presentations, and documents. A lighter GPT-5.4 mini is available to Free and Go users through the Thinking option.

When to use it

• Office-heavy work that also needs real reasoning, without flagship pricing.

GPT-Live-1 and GPT-Live-1 mini – OpenAI’s New Voice Models

What it is: Full-duplex voice models that can listen and speak at the same time, replacing Advanced Voice Mode as of July 8, 2026. GPT-Live-1 mini is the default for most users, GPT-Live-1 is available on paid tiers.

When to use it

• Any product built around live, spoken interaction. This is the direct successor to what “GPT-4o for real-time voice” used to mean in this guide.

Watch Out For

• If you’re building a voice interface today, evaluate GPT-Live, not GPT-4o. </mark>

GPT-5.3-Codex – Best for Agentic Software Engineering

OpenAI’s most capable agentic coding model to date, GPT-5.3-Codex combines the frontier coding performance of GPT-5.2-Codex with the reasoning and professional knowledge capabilities of GPT-5.2, all in one model that is also 25% faster than its predecessor.

This is the first OpenAI model that was instrumental in creating itself — the Codex team used early versions to debug its own training, manage deployment, and evaluate performance.

What makes it different from GPT-5.2-Codex:

• Advances both frontier coding performance and reasoning/professional knowledge in a single model
• 25% faster than GPT-5.2-Codex
• Takes on long-running, multi-day tasks involving research, tool use, and complex execution
• You can steer and interact with it while it’s working, without losing context
• State-of-the-art on SWE-Bench Pro (spanning Python, JS, Go, and Rust) and Terminal-Bench 2.0
• Achieves these results using fewer tokens than any prior model

When to use it:

• End-to-end software engineering tasks: building features, multi-file refactors, migrations
• Long-horizon work requiring research + code + validation in one session
• Computer use tasks: GPT-5.3-Codex can do nearly anything developers can do on a computer
• Web development, game development, and complex application scaffolding

Watch Out For:

• GPT-5.3-Codex is the first OpenAI model treated as “High capability” in cybersecurity under their Preparedness Framework — deployed with corresponding safeguards
• Pricing not yet officially announced at time of writing
• For real-time, rapid iteration, consider GPT-5.3-Codex-Spark instead

GPT-5.3-Codex-Spark – Best for Real-Time Coding Collaboration

GPT-5.3-Codex-Spark is a smaller, ultra-fast version of GPT-5.3-Codex designed specifically for real-time coding. It is the first OpenAI model to run on non-Nvidia hardware, powered by Cerebras’ Wafer Scale Engine 3 — a purpose-built AI accelerator enabling greater than 1,000 tokens per second output speed.

This marks the first milestone of OpenAI’s multi-year, $10B+ partnership with Cerebras.

Key Specs:

• Output speed: 1,000+ tokens/second (vs ~65 tok/s for the full GPT-5.3-Codex)
• Context window: 128K tokens (text-only; no image input)
• Time-to-first-token: reduced 50% via a new persistent WebSocket connection
• Hardware: Cerebras Wafer Scale Engine 3 (4 trillion transistors)

Benchmarks vs GPT-5.3-Codex:

• SWE-Bench Pro: Near-parity with the full model — strong real-world software engineering
• Terminal-Bench 2.0: 58.4% vs 77.3% for the full model (gap on complex multi-step terminal operations)

When to Use It:

• Interactive, real-time coding sessions where staying in flow matters
• Rapid prototyping and targeted edits
• Everyday coding assistance with near-instant responses
• Beginners or developers wanting a responsive AI coding partner

Watch Out For:

• Currently available only as a research preview for ChatGPT Pro subscribers ($200/month); not in the API
• Text-only input (no image support)
• Smaller model means it may struggle on the most complex, deep-reasoning terminal tasks
• Pricing not yet announced

GPT-5.2 – Best for Reliable Agentic Workflows

Note: GPT-5.2 was retired from ChatGPT on June 12, 2026. The section below is kept for reference and for anyone still using it via the API, current builds should default to GPT-5.5 or GPT-5.6 instead.

OpenAI’s current general-purpose flagship unified model is designed to be a dependable coding collaborator and agentic workhorse. GPT-5.2 builds on the GPT-5 line with more consistent instruction following, stronger multi-step execution, and improved reliability when coordinating tools, edits, and long-form workflows. It underpins the newest generation of the GPT-5 experience and is available in the API across variants (Instant for speed, Thinking for deeper reasoning, and Pro tiers where applicable).

When to use it

• One-model stacks where you want a single default for chat, coding, reasoning, and tool orchestration.
• Agentic systems that plan, call tools, validate outputs, and iterate—especially where execution quality matters more than raw speed.
• Complex workflows over large inputs (long tickets/specs, multi-file refactors, multi-step data transforms) where consistency and adherence to constraints is critical.
• High-stakes instruction following (strict formatting, policy guardrails, deterministic steps, QA checklists, acceptance criteria).

Strengths

• More faithful instruction following: better at sticking to constraints, formats, and “must/never” requirements across longer interactions.
• More reliable agent loops: improved at planning → acting → checking → revising without drifting, especially when tools are involved.
• Stronger “editor” ergonomics: better at iterative refinement (refactors, rewrites, patching) and maintaining coherence across multi-step changes.
• Unified capability profile: strong general reasoning plus practical execution—reduces the need to swap models mid-workflow.

Watch out for

• Output tokens can dominate cost on verbose tasks (long explanations, large code diffs, multi-turn agent traces). Profile your token mix early, and design for brevity (structured outputs, concise diffs, selective logging).
• Over-solving risk: for simple requests, consider routing to a faster/cheaper variant (e.g., “Instant” or a smaller model) and reserving deeper variants for genuinely complex work.
• Workflow discipline still matters: even with stronger reliability, you’ll get the best results by providing explicit acceptance criteria, test commands, and “definition of done” checklists.

GPT-5.1 — Enhanced Unified Model with Improved UX

Note: GPT-5.2 was retired from ChatGPT on June 12, 2026. The section below is kept for reference and for anyone still using it via the API, current builds should default to GPT-5.5 or GPT-5.6 instead.

What it is: OpenAI launched GPT 5.1 in November 2025, GPT-5.1 refines the GPT-5 foundation with a focus on improved conversational experience and enhanced personalization. It comes in two coordinated variants that work together:

• GPT-5.1 Instant: Warmer, more conversational, and better at following instructions. This is the most-used model, optimized for everyday tasks with a more natural, human-like tone.
• GPT-5.1 Thinking: Advanced reasoning model that dynamically adjusts thinking time based on complexity—much faster on simple tasks, more persistent on complex ones.

GPT-5.1 Auto automatically routes queries to the most suitable variant, providing an optimal balance of speed and capability.

Key Improvements Over GPT-5:

• Better Conversational Tone: More natural, warmer responses that feel less robotic
• Enhanced Customization: New personality presets (Professional, Candid, Quirky) in addition to existing options (Default, Nerdy, Cynical, Friendly, Efficient)
• Adaptive Reasoning: GPT-5.1 Thinking varies thinking time more dynamically—approximately twice as fast on simple tasks and twice as slow on complex ones compared to GPT-5 Thinking
• Clearer Responses: Less jargon, fewer undefined terms, making technical concepts more approachable
• Improved Instruction Following: Better at directly addressing user queries
• No Reasoning Mode for Developers: API users can set reasoning_effort to ‘none’ for latency-sensitive use cases while maintaining high intelligence

When to Use It:

• Default choice for most applications—chat, coding, analysis, and creative work
• When you need customizable tone and personality in responses
• Applications requiring both speed and advanced reasoning capabilities
• Building conversational AI that feels more human and engaging
• Coding tasks that benefit from improved personality and steerability

Strengths:

• Most refined user experience in the ChatGPT family
• Automatically balances speed and reasoning depth
• Strong performance across all benchmarks while feeling more natural
• Improved tool calling and code editing capabilities
• Better at parallel tool calling for agentic workflows
• Extended prompt caching (up to 24 hours) for cost efficiency

Watch Out For:

• GPT-5 models will remain available for 3 months to allow comparison and transition
• Output tokens still require cost consideration for high-volume applications

Availability:

• Rolling out to Pro, Plus, Go, and Business users first
• Free tier users receiving access gradually
• API access available as gpt-5.1-chat-latest
• Enterprise/Edu plans have a 7-day early access toggle

GPT-5 — Unified Default for New Builds

What it is: OpenAI’s current flagship is designed to be a coding collaborator and agentic workhorse. GPT-5 improves reliability and tool use and is positioned by OpenAI as the best model for end-to-end coding tasks and orchestrating multi-step workflows. It powers the latest ChatGPT experience and is available in the API. 

When to Use it

• Greenfield apps where you want one model for chat, coding, reasoning, and tool use.
• Agentic systems (plans, calls, tools, checks work) that benefit from stronger execution and editing on large codebases.

Strengths

• State-of-the-art on key coding benchmarks and markedly better “builder” ergonomics.
• Improved controllability and tool calling (e.g., “custom tools” in the API docs). 
• Other models in this family emphasize speed & cost vs. capacity; some GPT-5 and GPT-5 Pro also have massive context windows.

Watch Out For

• Output tokens are still costly, so you must profile your token mix and cache hit rates before using this model at scale.

GPT-4.1 — Long-Context and Robust Instruction Following

What it is: The 4.x line tuned for massive context and substantial coding/instruction following. It’s API-first and often chosen when you need to stuff lots of material into a single request. This is great for long coding tasks when you need the model to understand the entire codebase.

When to Use it

• Long-context RAG: whole codebases, dense contracts, multi-doc legal/finance reviews (≈ 1M-token window).
• Teams that need stable, predictable instruction following without the extra cost/latency of reasoning models.

Strengths

• Huge context + capable tool/use patterns; strong coding and editing performance at practical prices.

Watch Out for

• If you also need real-time voice/vision, you should use GPT-Live-1 for voice, or GPT-4o for vision + text

GPT-4o — Real-time, Native Multimodality (Voice/Vision/Text)

Note: As of July 2026, GPT-Live-1 and GPT-Live-1 mini have replaced Advanced Voice Mode for live spoken interaction. GPT-4o remains relevant for other real-time multimodal (vision + text) use cases below, but for voice specifically, see the GPT-Live-1 section above.

What it is: An end-to-end “omni” model that natively processes and emits text, images, and audio in a single network—great for apps that feel conversational and live.

When to use it

• Real-time assistants: talk to the model, show it your screen or images, get voice back with human-like pacing (audio response as low as ~232 ms, ~320 ms avg).
• Multimodal UX (vision + text) where latency matters more than ultra-long context.

Strengths

• Smooth, interruptible voice; strong vision; broadly “GPT-4-level” text/code quality but faster and cheaper than earlier 4-series.

Watch Out For

• For million-token context or massive document ingestion, use GPT-4.1; for the most complex logic tasks, consider the o-series or GPT-5.

o-Series (o1 / o3 / o4-mini) — Reasoning-First Models

What they are: Models trained to think before answering. These models spend extra computing time in inference to solve harder problems (math, science, multi-step logic). This line began with o1 and continued with o3 and o4-mini.

When to Use Them

• Complex STEM, program synthesis/repair, proofs, analytical planning, where step-by-step reasoning quality is paramount.

Strengths

• Substantial gains on difficult benchmarks (coding/math/vision) versus generalist models; explicitly designed for multi-step analysis.

Watch Out For

• These models take more time and cost more due to “thinking.” GPT-5 or GPT-4.1 may be more cost-effective if you don’t need deep reasoning.

GPT-3.5 Turbo — Legacy, Budget Workhorse

What it is: The aligned, instruction-following evolution of GPT-3 (InstructGPT/RLHF) that powered the original ChatGPT research preview. It remains available as a cheaper text model in the API.

When to use it

• High-volume, low-stakes text tasks: basic chat, templated replies, simple classification/formatting where top-tier accuracy isn’t required.

Strengths

• Low cost; familiar behavior on instruction-following tasks.

Watch-outs

• Noticeably weaker on complex reasoning, coding, and factual reliability compared to GPT-4.x, o-series, and GPT-5. (Consider upgrading for anything mission-critical.)

Quick Summary

Use Case	Recommended Model
Frontier reasoning, long-horizon agentic work	GPT-5.6 Sol
Balanced production work at lower cost	GPT-5.6 Terra
High-throughput, cost-sensitive tasks	GPT-5.6 Luna
Live, spoken conversation	GPT-Live-1 / GPT-Live-1 mini
Agentic coding, multi-day software engineering	GPT-5.3-Codex
Real-time coding, rapid iteration	GPT-5.3-Codex-Spark (Pro users)
General chat, knowledge work, multi-step tasks	GPT-5.5 (was GPT-5.2, now retired)
Office work + reasoning (sheets, slides, docs)	GPT-5.4
Conversational AI with great UX	GPT-5.1 (retired Mar 11, 2026, see GPT-5.5)
Long-context RAG, codebases, multi-doc legal	GPT-4.1
Real-time voice/vision interaction	GPT-4o (voice role now handled by GPT-Live-1)
Mathematical proofs, research, explicit reasoning	o-series (o3/o1/o4-mini)
Budget / high-volume basic chat	GPT-3.5 Turbo

Also Read:

1. How to Build Enterprise Customer Service Chatbots with ChatGPT
2. How to Use ChatGPT for Documents
3. Integrate Kommunicate Chatbot with ChatGPT for Seamless Experience

Some Things to Remember

There are some rules that we always keep in mind before incorporating a model into Kommunicate. These reduce the overall costs of your applications and make it easy to use:

• Estimate token mix (input vs output) + enable prompt caching: Extended caching in GPT-5.1 now supports up to 24-hour retention
• Set Guardrails: Maintain refusal policies, sensitive data handling, and redaction.
• Choose Latency Class: Choose between real-time and batch with set timeouts/retries.
• Add a Fallback Model & Circuit Breaker: This helps with rate limits/outages.
• Log Prompts/Outputs with PII scrubbing and Evaluation Hooks: This will reduce the lag risks and provide data safety for your customers and clients.
• Track Costs – Maintain a dashboard for costs to track the overall costs of your models.
• Run Evals When You Change Models: Every model has different capabilities and strengths, and whenever you change the model, it’s necessary to test them at every step.

Finally, now that we understand the strengths, capabilities, and costs of all the ChatGPT OpenAI models, let’s talk about how they’re used in real-life applications.

Which OpenAI Model Should You Use?

We’ve created a small tool to help you choose the best model for your use case:

Frequently Asked Questions

What is the newest ChatGPT model? +

GPT-5.6 Sol, released July 9, 2026, is OpenAI’s newest and most capable model.

Is GPT-5.2 still available? +

No. GPT-5.2 was retired from ChatGPT on June 12, 2026. Conversations rolled over to GPT-5.5.

What model does ChatGPT use by default? +

GPT-5.5 Instant is the current default for everyday ChatGPT conversations.

Which ChatGPT model is best for coding? +

GPT-5.3-Codex remains the specialist pick for long-horizon software engineering.

Which ChatGPT model is best for voice conversations? +

GPT-Live-1 and GPT-Live-1 mini, which replaced Advanced Voice Mode on July 8, 2026.

Conclusion

As of today, OpenAI’s model landscape has expanded significantly:

• GPT-5.6 Sol is now OpenAI’s flagship for the hardest reasoning and long-running agentic work, released July 9, 2026.
• GPT-5.5 is the current ChatGPT default, after GPT-5.2’s retirement in June 2026.
• GPT-5.4 folds Codex-level coding into a generalist model, strong for office-heavy work.
• GPT-5.3-Codex remains the specialist pick for serious, professional software engineering.
• GPT-Live-1 now handles real-time voice, replacing GPT-4o’s role there. GPT-4.1 still handles massive long-context needs, and the o-series remains best for deliberate, tunable reasoning.

The pace of releases hasn’t slowed down. GPT-5.4, GPT-5.5, and the full GPT-5.6 family all shipped within about four months, on top of GPT-5.2, GPT-5.2-Codex, GPT-5.3-Codex, and GPT-5.3-Codex-Spark before that. The key skill is no longer just “pick the right model,” it’s designing your stack to absorb a retirement or a new release without a rebuild.

Meanwhile, if you need help with building a generative AI chatbot for customer service. Feel free to sign up for Kommunicate!