Head-to-Head
Claude 3.5 Sonnet vs GPT-4o
A working comparison of Anthropic's Claude 3.5 Sonnet and OpenAI's GPT-4o across reasoning, coding, vision, context, latency, safety, and price — synthesised from each lab's published model cards and public benchmark reports.
Updated 2026-06-10
Pick Claude 3.5 Sonnet for
- • Long-context document and codebase reasoning (200K tokens)
- • Agentic, multi-file coding work (SWE-bench Verified leader)
- • Careful written analysis, drafting, and refactoring
- • Document and chart understanding (DocVQA)
Pick GPT-4o for
- • Voice and realtime multimodal experiences
- • Image + audio + video frame inputs in a single model
- • Lowest per-token cost at scale
- • Math-heavy benchmarks and structured outputs
| Dimension | Claude 3.5 Sonnet | GPT-4o |
|---|---|---|
| Developer | Anthropic | OpenAI |
| Release | June 2024 (3.5), upgraded Oct 2024 | May 2024, refreshed through 2025 |
| Context window | 200K tokens | 128K tokens |
| Max output | 8,192 tokens (beta 200K) | 16,384 tokens |
| Multimodal input | Text + image | Text + image + audio + (video frames) |
| Voice / realtime | Not native | GPT-4o Realtime API |
| Reasoning (MMLU) | ~88.7% | ~88.7% |
| Graduate reasoning (GPQA) | ~59% | ~53% |
| Math (MATH) | ~71% | ~76% |
| Coding (HumanEval) | ~92% | ~90% |
| Agentic coding (SWE-bench Verified) | ~49% | ~33% |
| Vision (MMMU) | ~68% | ~69% |
| Document/chart (DocVQA) | ~95% | ~92% |
| Latency (TTFT) | Fast | Very fast (optimized for realtime) |
| Tool use / function calling | Yes, parallel + computer use (beta) | Yes, parallel + structured outputs |
| Input price | $3 / 1M tokens | $2.50 / 1M tokens |
| Output price | $15 / 1M tokens | $10 / 1M tokens |
| Safety posture | Constitutional AI, ASL-2 deployment | RLHF + Model Spec, system-card evaluations |
Reasoning
On the headline reasoning benchmark (MMLU 5-shot) the two models are effectively tied near 89%. The gap opens on graduate-level science questions (GPQA Diamond), where Claude 3.5 Sonnet leads by several points. GPT-4o regains ground on competition mathematics (MATH), where its chain-of-thought tends to produce more disciplined symbolic manipulation.
Coding
HumanEval is close; the meaningful gap is on agentic coding. On SWE-bench Verified — real GitHub issues across full repositories — Claude 3.5 Sonnet resolves substantially more issues than GPT-4o. For copilots that need to plan edits across files and run tests, Claude is the stronger default. GPT-4o stays competitive on single-file completions and structured-output pipelines.
Vision and multimodality
Both models score in the high 60s on MMMU. Claude has a small edge on dense document understanding (DocVQA, chart reading). GPT-4o is the broader multimodal model — it adds native audio in and out, low-latency voice via the Realtime API, and image generation in the same model family. For any product where voice or video is core, GPT-4o is the obvious pick.
Context, latency, and price
Claude's 200K context lets you skip retrieval for many medium-sized corpora; GPT-4o's 128K is still generous. GPT-4o is faster to first token and roughly 30–40% cheaper per output token, which compounds at scale. Many production teams route by task: GPT-4o for interactive UX and voice, Claude 3.5 Sonnet for long-context analysis and agentic coding.
Safety and governance
Anthropic frames Claude under Constitutional AI and ships it at ASL-2 with a Responsible Scaling Policy. OpenAI publishes a Model Spec and system cards for each GPT-4o release. Both publish red-team evaluations; neither is suitable for high-stakes autonomous action without human oversight.
FAQ
- Is Claude 3.5 Sonnet better than GPT-4o for coding?
- On agentic coding benchmarks like SWE-bench Verified, Claude 3.5 Sonnet substantially outperforms GPT-4o (~49% vs ~33%), and edges it on HumanEval. For real-world refactors across multi-file repositories, Claude is the stronger default; GPT-4o is competitive on isolated snippets and faster to first token.
- Which model has the larger context window?
- Claude 3.5 Sonnet supports 200K input tokens versus GPT-4o's 128K. For long PDFs, codebases, or transcripts, Claude fits more context in a single request without retrieval-augmented chunking.
- Does Claude support voice or video like GPT-4o?
- No. GPT-4o is natively multimodal across text, image, and audio (with a low-latency Realtime API). Claude 3.5 Sonnet accepts text and image input only — voice apps are typically GPT-4o territory.
- Which is cheaper?
- GPT-4o is cheaper per token: $2.50/$10 per million input/output tokens versus Claude 3.5 Sonnet's $3/$15. At scale, GPT-4o wins on raw cost; Claude can still be cheaper end-to-end if its longer context reduces retrieval overhead.
- Which should I pick?
- Pick Claude 3.5 Sonnet for long-context document work, agentic coding, and careful written reasoning. Pick GPT-4o for voice, realtime UX, image-heavy multimodal apps, and the lowest per-token cost. Many production stacks route between the two by task.
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