BlogLLM Benchmark Scores as Published, Side by Side

Mistral Medium 3.5: Benchmark Scores as Published

Every result the catalog holds for Mistral Medium 3.5: 16 tests in 7 areas, from 4 pages. All were printed by Mistral AI itself. Each number is as printed; nothing is ranked or rescored.

Developer Mistral AIReleased 2026-05-22Context window 256KInput Text, imageOutput TextWeights Open (Modified MIT License)Data version 2026103001, as of 2026-10-30

Knowledge Work

Agentic Coding

TestValuePrinted bySetup as printed
SWE-bench Verified77.6%Mistral AI, Mistral Medium 3.5 model cardchecked 2026-10-15Effort: max

Science and Math

TestValuePrinted bySetup as printed
AIME 202586.3%Mistral AI, Mistral Medium 3.5 model cardchecked 2026-10-15Effort: max
SciCode-Verified70%Mistral AI, Mistral Large 4 (preview)checked 2026-10-15Attempt budget: pass@1 (n=6)
BeyondAIME66.9%Mistral AI, Mistral Medium 3.5 model cardchecked 2026-10-15Effort: max

Multimodal Understanding

TestValuePrinted bySetup as printed
ChartQA Pro55.4%Mistral AI, Mistral Large 4 (preview)checked 2026-10-15-

Tool Use and Workflows

TestValuePrinted bySetup as printed
τ³-bench Banking13.4%Mistral AI, Mistral Medium 3.5 model cardchecked 2026-10-15Effort: max; Harness: gpt-5.2 user simulator (low), 4 trials; terminal- or embedding-based agentic search retrieval, highest score
τ³-bench Airline72%Mistral AI, Mistral Medium 3.5 model cardchecked 2026-10-15Effort: max; Harness: gpt-5.2 user simulator (low), 4 trials; Sierra-reported for Claude Sonnet 4.5 and Qwen3.5
τ³-bench Retail76.1%Mistral AI, Mistral Medium 3.5 model cardchecked 2026-10-15Effort: max; Harness: gpt-5.2 user simulator (low), 4 trials; Sierra-reported for Claude Sonnet 4.5 and Qwen3.5
τ³-bench Telecom91.4%Mistral AI, Mistral Medium 3.5 model cardchecked 2026-10-15Effort: max; Harness: gpt-5.2 user simulator (low), 4 trials; Sierra-reported for Claude Sonnet 4.5 and Qwen3.5

Web Search and Research

TestValuePrinted bySetup as printed
BrowseComp48.6%Mistral AI, Mistral Medium 3.5 model cardchecked 2026-10-15Effort: max; Harness: context management, discard-all at 100k tokens (Mistral)

Instruction Following

TestValuePrinted bySetup as printed
IFBench69Mistral AI, Mistral Medium 3.5 model cardchecked 2026-10-15Effort: max
COLLIE95.8%Mistral AI, Mistral Medium 3.5 model cardchecked 2026-10-15Effort: max

Price

API list prices in US dollars per one million tokens, as printed on the developer's pricing page on the day checked. Cost per task is measured by Vals AI.

PriceValuePrinted bySetup as printed
Input$1.5Mistral AI, Mistral API pricingchecked 2026-10-15-
Cached input$0.15Mistral AI, Mistral API pricingchecked 2026-10-19-
Output$7.5Mistral AI, Mistral API pricingchecked 2026-10-15-
Cost per taskVals AI, USD, lower is better$16.74Vals AI, Vibe Code Bench v1.1 leaderboardchecked 2026-10-27Harness: OpenHands

More from Mistral AI

Every number here is read from the same catalog file as the benchmark table, data version 2026103001. Where one page printed the model under several setups, each value is listed. The catalog is public in armanobosyan/sugra-llm-benchmarks; a wrong number can be reported from the table, with Report an error under the value, or as an issue in that repository.