o3-minivsQwen3.7-Max
o3-mini | Qwen3.7-Max | |
|---|---|---|
| API pricingUSD per 1M tokens · lower wins | ||
Input priceWhat you pay for everything you send the model — your question, plus any documents or earlier conversation you include with it. | $1.10 | $2.50 |
Output priceWhat you pay for the text the model writes back. It is normally the dearer half: producing an answer costs more than reading one. | $4.40 | $7.50 |
Cached input priceA reduced rate for text you send over and over. If every request starts with the same instructions or the same document, the provider keeps a copy ready and charges less to read it again. | $0.55 | — |
| Benchmarks | ||
SWE-Bench VerifiedCoding — Real coding tasks pulled from open-source projects — the AI has to find and fix actual bugs. A human-checked version of the original SWE-Bench. Higher is better. | 49.3% | 80.4% |
| BenchmarksPublished by one model only | ||
BullshitBench v2Nonsense detection — Given a confidently-worded but nonsensical prompt, does the AI spot that it makes no sense and push back — instead of playing along and inventing an answer? The score is how often it clearly called out the nonsense. Higher is better. | — | 71% |
SWE-Bench ProAgentic coding — Can the AI fix real bugs in real software? It's handed actual problems from open-source projects and has to write code that genuinely solves them. Higher is better. | — | 60.6% |
LiveCodeBenchCompetitive coding — Coding problems published so recently the AI can't have seen them in training — a contamination-free test of raw programming skill. Higher is better. | — | 91.6% |
Terminal-Bench 2.0Agentic terminal coding — Can the AI work in a command-line terminal — running commands and finishing technical setup tasks the way a developer would? (Version 2.0 of the test.) Higher is better. | — | 69.7% |
MCP AtlasMulti-step tool use — Can the AI chain together many tools and steps to complete one bigger task, rather than doing just a single thing? Higher is better. | — | 76.4% |
Humanity's Last Exam · with toolsMultidisciplinary reasoning — Humanity's Last Exam — extremely hard expert questions across many subjects. “With tools” means the AI is allowed to search the web or run code while answering. Higher is better. | — | 41.4% |
GPQA DiamondScience — Graduate-level science questions in biology, physics, and chemistry — hard enough that subject-matter PhDs score around 65%. Higher is better. | — | 92.4% |
| Overview | ||
| Company | OpenAI | Qwen |
| Release date | Jan 31 2025 | May 20 2026 |
| Access | Proprietary | Proprietary |
Other comparisons
Frequently asked questions
Qwen3.7-Max leads o3-mini on 1 of the 1 benchmark they both report (SWE-Bench Verified). o3-mini is cheaper on both input and output: $1.10 vs $2.50 per million input tokens, and $4.40 vs $7.50 per million output tokens. o3-mini shipped 474 days before Qwen3.7-Max, so benchmark comparisons should account for the intervening progress.
Published specifications for these two models are limited — see each model page for the latest details.
On SWE-Bench Verified, Qwen3.7-Max leads at 80.4% vs o3-mini at 49.3%.
o3-mini was released by OpenAI on Jan 31 2025.
Qwen3.7-Max was released by Qwen on May 20 2026.
Qwen3.7-Max leads on SWE-Bench Verified — o3-mini 49.3% vs Qwen3.7-Max 80.4%.
o3-mini is cheaper on both input and output: $1.10 vs $2.50 per million input tokens, and $4.40 vs $7.50 per million output tokens. Rates are pay-as-you-go API prices verified on August 18, 2026.