If you opened your code editor this month and paused to wonder whether to point it at Claude or ChatGPT, you are not alone. Anthropic shipped Claude Sonnet 5 on June 30, 2026, and it immediately became the first model to break 80% on the industry’s toughest coding benchmark. That reignited a very practical question for working developers: is Sonnet 5 now the model to beat, or does OpenAI’s GPT-5.4 still deserve to be your default?
This comparison is written for developers, technical founders, and engineering leads who have to pick one model as their day-to-day coding assistant and then justify the bill. By the end you will know exactly where each model wins, where the pricing traps hide, and which one to choose for your specific situation. If you would rather answer a few quick questions and get a personalized pick, try our which AI is right for you quiz.
The 30-second verdict
Here is the short version. On raw coding accuracy the two models are effectively tied — both land in the mid-80s on SWE-bench Verified, the benchmark that asks a model to fix real GitHub issues. The decision that actually matters comes down to cost behavior, output speed, and how heavily you lean on autonomous, multi-step “agentic” coding. Claude Sonnet 5 is the sharper agentic workhorse and the cheaper option during its introductory window. GPT-5.4 is the more versatile generalist, with native computer use and full-resolution vision. Neither is a wrong answer — they are wrong for different jobs.
Claude Sonnet 5 vs GPT-5.4: the head-to-head
Both models are frontier-class and both will write good code. The table below scores them on the seven criteria that decide real projects — accuracy, hard-task performance, price, context, speed, agentic tool use, and ideal workload — with the edge and the catch for each row.
| Criteria | Claude Sonnet 5 | GPT-5.4 | Edge & caveat |
|---|---|---|---|
| Coding accuracy (SWE-bench Verified) | ~82–85% | ~84% | Tie — inside the margin of error |
| Hard real-world tasks (SWE-bench Pro) | 63.2% | 57.7% | Sonnet 5; Pro is new and scores still move |
| Price (standard, per 1M in/out) | $3 / $15 ($2 / $10 intro to Aug 31) | $2.50 / $15 | GPT-5.4 on sticker; Sonnet cheaper during intro |
| Context window | 1M tokens | 1M tokens (272K standard) | Tie; GPT bills 2x input above 272K |
| Output speed | Tuned for fast throughput | Slower at high reasoning | Sonnet 5; GPT digs deeper given time |
| Agentic / tool use | Terminal-Bench 80.4, OSWorld 81.2 | Native computer use + vision | Split: Sonnet for code agents, GPT for computer control |
| Best use case | Long autonomous coding runs | Versatile reasoning + vision | Depends on your workload |
Where each model pulls ahead
Coding accuracy is a near-tie
The headline is that Sonnet 5 cleared 80% on SWE-bench Verified for the first time in the industry, scoring in the low-to-mid 80s depending on how much “thinking” budget you allow. GPT-5.4 sits at roughly 84% on the same test. In other words, they are separated by noise, not by a moat. The gap widens slightly on the newer, harder SWE-bench Pro, where Sonnet 5 (63.2%) leads GPT-5.4 (57.7%) — a hint that Sonnet is a little more reliable on gnarly, multi-file changes. As The Register put it in its July 1 review, Sonnet 5 “heads straight down the middle of the road,” meaning it is broadly capable with few surprises rather than a spiky specialist.
The price story hides a tokenizer catch
On paper GPT-5.4 is a touch cheaper: $2.50 per million input tokens against Sonnet 5’s standard $3. But Anthropic is running introductory pricing of $2 / $10 through August 31, 2026, which flips the math in Sonnet’s favor for now. Two caveats decide your real bill. First, Sonnet 5 ships with a new tokenizer that can map the same text to 1.0–1.35x more tokens, quietly inflating cost. Second, GPT-5.4 charges 2x input and 1.5x output once a session crosses 272K tokens. If you run big-context agents, model those multipliers before you commit — our guide on cutting AI token costs walks through the math.
Speed, context, and agentic behavior
Both models now offer a 1M-token context window, so whole-repo prompts are on the table for either one (GPT-5.4 defaults to 272K and needs Codex or Azure configuration to reach the full million). Where they diverge is temperament. Sonnet 5 is tuned for fast, direct output and long autonomous runs; early reviewers describe the useful pattern as “it keeps going, verifies more, and reaches a finished result with fewer nudges.” GPT-5.4 counters with native computer use, full-resolution vision, and tool search — strengths that matter if your agent has to click around a screen, not just edit files. One developer’s rule of thumb is worth remembering: “If you’re doing something hard, just use a bigger model,” because Sonnet 5 on maximum thinking effort can approach Opus-level cost.
Best for: the verdict on each model
Claude Sonnet 5 is best for…
Teams that live inside coding agents. If your work is CI automation, long refactors, test-and-fix loops, or anything running through Claude Code, Sonnet 5 is the pragmatic default: fast, cost-controlled, and better at staying on plan across multi-step changes. It is also the model most people should try first because it is now the default on Claude’s Free and Pro plans, so the barrier to a real test is essentially zero.
GPT-5.4 is best for…
Developers who need more than code. GPT-5.4’s native computer use, full-resolution vision, and deep reasoning make it the stronger pick for mixed workloads — scraping a UI, reading screenshots, or blending research with implementation. It is also the safe institutional choice if your stack already runs on OpenAI or Azure. Note that OpenAI has since shipped the GPT-5.5 and GPT-5.6 (Luna, Terra, Sol) tiers in limited preview, which positions GPT-5.4 as the mature, cost-quality sweet spot rather than the bleeding edge.
Quick recommendation by user type
- Beginner or hobbyist: Start with Claude Sonnet 5. It is the default on free and Pro plans, gives fast feedback, and forgives vague prompts — the cheapest way to learn.
- Pro or solo developer: Choose by workload. Pick Sonnet 5 for agentic coding and Claude Code; pick GPT-5.4 if you need vision or computer use, or already live in the OpenAI ecosystem. Still torn across the wider field? See our Gemini vs Claude vs GPT model picker.
- Team or enterprise: Run both and route by task. Standardize on Sonnet 5 for CI and agent automation to control spend, and keep GPT-5.4 on hand for research, vision, and computer-use jobs.
Frequently asked questions
Is Claude Sonnet 5 better than GPT-5.4 for coding?
They are roughly tied on SWE-bench Verified. Sonnet 5 edges the harder SWE-bench Pro test and long agentic runs, while GPT-5.4 wins on vision and computer use. Choose by workload rather than a single benchmark number.
Which is cheaper, Sonnet 5 or GPT-5.4?
GPT-5.4 is slightly cheaper on sticker price ($2.50 vs $3 per million input tokens), but Sonnet 5 is cheaper during its introductory pricing of $2 / $10 through August 31, 2026. Watch Sonnet’s new tokenizer and GPT-5.4’s surcharge above 272K tokens, both of which change the real cost.
What is SWE-bench Verified and why does it matter?
It is a benchmark built from real GitHub issues that a model must actually fix, making it the closest public proxy for day-to-day software work. Sonnet 5 was the first model to break the 80% mark on it.
Should I wait for GPT-5.5 or GPT-5.6 instead?
Those are OpenAI’s newer premium tiers, with the GPT-5.6 Sol, Terra, and Luna models in limited preview. For most production coding, GPT-5.4 remains the cost-quality sweet spot, so there is no need to wait unless you specifically need the top-tier reasoning.
Can I switch between them without rewriting my code?
Mostly yes. Both expose familiar APIs and million-token contexts, but expect to lightly tune prompts and tool definitions, and remember that token accounting differs between the two, so re-check your cost estimates after switching.