Compare AI models
| 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. | $5.00 | $0.15 |
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. | $25.00 | $0.60 |
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. | $0.50 | — |
Cheapest inputLowest input rate across third-party providers, excluding the lab itself. The cheapest endpoint may run a quantised build or a shorter context — see "Available from" on the model page. | $5.00Amazon Bedrock | $0.15Mistral |
Cheapest outputLowest output rate across third-party providers, excluding the lab itself. May come from a different provider than the cheapest input. | $25.00Amazon Bedrock | $0.60Mistral |
| Benchmarks | ||
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. | 90% | 6% |
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. | 80.9% | — |
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. | 30.8% | — |
GPQA DiamondScience — Graduate-level science questions in biology, physics, and chemistry — hard enough that subject-matter PhDs score around 65%. Higher is better. | 87% | — |
OSWorld-VerifiedAgentic computer use — Can the AI actually operate a computer — clicking, typing, and using real apps — to finish tasks on its own? Higher is better. | 66.3% | — |
threejsevalCommunity preference (Three.js) — Every model gets the same prompt — "the Eiffel Tower", "a glass fishbowl", "a robot arm picking toys into a box" — and builds a 3D scene in Three.js. Real people then see two scenes side by side, names hidden, and vote for the one they prefer. The votes become a chess-style Elo rating on threejseval.com, averaged across all the prompts. It measures whether the scene looks and moves right to a human eye, not whether the code passes a test. Higher is better. | 1147 | — |
| Overview | ||
| Company | Anthropic | Mistral |
| Release date | Nov 24 2025 | Mar 16 2026 |
| Access | Closed | Closed |
| Model details | View model | View model |
Other comparisons
Claude Opus 4.5vsGPT-6.1 SolMistral Small 4vsGPT-6.1 SolClaude Opus 4.5vsGemini 4 ArgonMistral Small 4vsGemini 4 ArgonClaude Opus 4.5vsMuse Spark 1.3Mistral Small 4vsMuse Spark 1.3Claude Opus 4.5vsGrok 4.7Mistral Small 4vsGrok 4.7Claude Opus 4.5vsDeepSeek-V4.1-FlashMistral Small 4vsDeepSeek-V4.1-FlashClaude Opus 4.5vsKimi K3Mistral Small 4vsKimi K3Frequently asked questions
Claude Opus 4.5 leads Mistral Small 4 on 1 of the 1 benchmark they both report (BullshitBench v2). Mistral Small 4 is cheaper on both input and output: $0.15 vs $5.00 per million input tokens, and $0.60 vs $25.00 per million output tokens. Claude Opus 4.5 shipped 112 days before Mistral Small 4, 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 BullshitBench v2, Claude Opus 4.5 leads at 90% vs Mistral Small 4 at 6%.