Quality
#26/6729.9
Overall quality score
See how Mistral: Mistral Medium 3.5 compares with other broadly useful AI models across quality, speed, price, context, and practical capabilities.
29.9
Overall quality score
35 t/s
Output tokens per second
$1.50/1M
Per 1M tokens
$7.50/1M
Per 1M tokens
262.1K
Content read at once
Mistral: Mistral Medium 3.5 ranks #26 of 67 for overall quality and #50 for response speed in the current catalogue.
Its listed input price is $1.50/1M, output price is $7.50/1M, and it can work with up to 262.1K of context at once.
Its strongest areas in the current data are coding, math and logic, following instructions.
Named evaluation records for technical comparison. Results retain their original benchmark names and sources.
| Benchmark | Area | Mistral Medium 3.5 | Source |
|---|---|---|---|
| Intelligence Index | overallQuality | 29.9 | OpenRouter / artificial-analysis |
| Coding Index | coding | 46.9 | OpenRouter / artificial-analysis |
| Agentic Index | agentic | 19 | OpenRouter / artificial-analysis |
| GPQA | GPQA Diamond | 74.8 | OpenRouter model benchmarks |
| Humanity's Last Exam | HLE | 12.8 | OpenRouter model benchmarks |
| IFBench | IFBench | 68.8 | OpenRouter model benchmarks |
| τ²-Bench Telecom | τ²-Bench Telecom | 94.2 | OpenRouter model benchmarks |
| AA-LCR | AA-LCR | 61 | OpenRouter model benchmarks |
| GDPval-AA | GDPval-AA | 21.6 | OpenRouter model benchmarks |
| CritPt | CritPt | 0 | OpenRouter model benchmarks |
| SciCode | SciCode | 39.6 | OpenRouter model benchmarks |
| Terminal-Bench Hard | Terminal-Bench Hard | 33.3 | OpenRouter model benchmarks |
| AA-Omniscience Accuracy | AA-Omniscience Accuracy | 25.1 | OpenRouter model benchmarks |
| AA-Omniscience Non-Hallucination Rate | AA-Omniscience Non-Hallucination Rate | 18 | OpenRouter model benchmarks |
Quality benchmarks
The darker bar marks Mistral: Mistral Medium 3.5; the lighter bars provide context from other leading models.
Overall capability · Higher is better
Output tokens per second · Higher is better
USD per 1M tokens · Lower is better