Kimi K2 0711 vs Mistral Medium 3
Updated October 21, 2026. 17 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
Neither model has a coding score yet, so the two cannot be ranked on coding.
Kimi K2 0711 has the edge where what matters is Design Arena: websites or Design Arena: game dev, where it leads.
- Shared results
- 17
- Kimi K2 0711 only
- 19
- Mistral Medium 3 only
- 40
- Like-for-like categories
- 8 of 9
Shared results can support a head-to-head reading. Results only one model has describe coverage, not superiority.
Which one for your work
Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.
Coding
Vibe Coding Index, six public coding benchmarks
No call
Neither has a coding score yet.
One side not measured
Intelligence
AA Intelligence Index
Kimi K2 0711
Kimi K2 0711 leads, 12.7 against 9.0.
Same board, both measured
Reasoning
GPQA Diamond
No call
Only Kimi K2 0711 has a GPQA Diamond result, 71.5%.
Directional only
Math
AIME
No call
Only Kimi K2 0711 has a AIME result, 62.7%.
Directional only
Knowledge
MMLU Pro
No call
Only Kimi K2 0711 has a MMLU Pro result, 79.4%.
Directional only
Web design
Design Arena: websites
Mistral Medium 3
Mistral Medium 3 leads, 1079 against 1050.
Same board, both measured
Long documents
Listed context window
No call
Both take 131K tokens.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Mistral Medium 3
Kimi K2 0711 $0.0017, Mistral Medium 3 $0.0014 per turn.
List prices
At a glance
- Coding index
- Kimi K2 0711 not benchmarked, Mistral Medium 3 not benchmarked.
- Widest category
- Agentic work, 36.8 points apart on average over 1 shared benchmark.
- Widest single gap
- τ²-Bench Telecom: Kimi K2 0711 61.1% against Mistral Medium 3 24.3%, 36.8 points apart on a 0 to 100 scale.
- Output price
- Kimi K2 0711 $2.30 against Mistral Medium 3 $2.00 per million output tokens, 1.1x apart.
- Context window
- Both take 131K tokens.
Benchmark by benchmark
First the score: boards each model leads, per category, where both have a result. Then every board, a category to a fold; bars are each result on a 0 to 100 scale, so compare the two in a row, not one row with another.
| Category | Kimi K2 0711 | Bars | Mistral Medium 3 | Ties |
|---|---|---|---|---|
| Coding | 2 | 0 | ||
| Intelligence | 2 | 0 | ||
| Agentic work | 1 | 0 | ||
| Reasoning | 2 | 0 | ||
| Math | 2 | 0 | ||
| Knowledge | 1 | 0 | ||
| Web design | 1 | 4 | ||
| General | 2 | 0 | ||
| All shared boards | 13 | 4 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index20
| Benchmark | Kimi K2 0711 | Mistral Medium 3 | Leader |
|---|---|---|---|
| Aider polyglot | 59.1% | Not measured | Only Kimi K2 0711 measured |
| SWE-bench Verified | 71.2% | Not measured | Only Kimi K2 0711 measured |
| LiveCodeBench (Vals AI) | 70.5% | Not measured | Only Kimi K2 0711 measured |
| LiveCodeBench (Artificial Analysis run) | 55.6% | 40.0% | Kimi K2 0711 |
| Terminal-Bench Hard (Artificial Analysis run) | 15.9% | 3.8% | Kimi K2 0711 |
| Terminal-Bench | 27.8% | Not measured | Only Kimi K2 0711 measured |
| GSO-Bench | 4.9% | Not measured | Only Kimi K2 0711 measured |
| WeirdML | 39.4% | Not measured | Only Kimi K2 0711 measured |
| LMArena Text: coding | Not measured | 1385 | Only Mistral Medium 3 measured |
| LMArena Text: software and IT | Not measured | 1385 | Only Mistral Medium 3 measured |
| Neither model has a result on the other 28 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Kimi K2 0711 | Mistral Medium 3 | Leader |
|---|---|---|---|
| AA Intelligence Index | 12.7 | 9.0 | Kimi K2 0711 |
| Epoch Capabilities Index | 140.0 | 134.0 | Kimi K2 0711 |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Kimi K2 0711 | Mistral Medium 3 | Leader |
|---|---|---|---|
| τ²-Bench Telecom | 61.1% | 24.3% | Kimi K2 0711 |
| Neither model has a result on the other 38 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Kimi K2 0711 | Mistral Medium 3 | Leader |
|---|---|---|---|
| GPQA Diamond | 71.5% | Not measured | Only Kimi K2 0711 measured |
| GPQA Diamond (Artificial Analysis run) | 76.6% | 57.8% | Kimi K2 0711 |
| Humanity's Last Exam (Artificial Analysis run) | 7.4% | 4.1% | Kimi K2 0711 |
| SimpleBench | 26.3% | Not measured | Only Kimi K2 0711 measured |
| LMArena Text: hard prompts | Not measured | 1364 | Only Mistral Medium 3 measured |
| LMArena Text: expert | Not measured | 1342 | Only Mistral Medium 3 measured |
| LMArena Text: hard prompts in English | Not measured | 1374 | Only Mistral Medium 3 measured |
| LMArena Vision: diagrams | Not measured | 1155 | Only Mistral Medium 3 measured |
| LMArena Vision: homework | Not measured | 1165 | Only Mistral Medium 3 measured |
| Neither model has a result on the other 12 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Kimi K2 0711 | Mistral Medium 3 | Leader |
|---|---|---|---|
| AIME | 62.7% | Not measured | Only Kimi K2 0711 measured |
| MATH 500 (Vals AI) | 94.2% | Not measured | Only Kimi K2 0711 measured |
| MGSM (Vals AI) | 91.0% | Not measured | Only Kimi K2 0711 measured |
| AA Math Index | 57.0 | 30.3 | Kimi K2 0711 |
| AIME 2025 (Artificial Analysis run) | 57.0% | 30.3% | Kimi K2 0711 |
| LMArena Text: math | Not measured | 1353 | Only Mistral Medium 3 measured |
| LMArena Text: mathematical work | Not measured | 1354 | Only Mistral Medium 3 measured |
| Neither model has a result on the other 6 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Kimi K2 0711 | Mistral Medium 3 | Leader |
|---|---|---|---|
| MMLU Pro | 79.4% | Not measured | Only Kimi K2 0711 measured |
| LegalBench (Vals AI) | 81.5% | Not measured | Only Kimi K2 0711 measured |
| CorpFin (Vals AI) | 50.4% | Not measured | Only Kimi K2 0711 measured |
| TaxEval (Vals AI) | 70.2% | Not measured | Only Kimi K2 0711 measured |
| MedQA (Vals AI) | 84.0% | Not measured | Only Kimi K2 0711 measured |
| MMLU Pro (Artificial Analysis run) | 82.4% | 76.0% | Kimi K2 0711 |
| LMArena Text: science | Not measured | 1381 | Only Mistral Medium 3 measured |
| LMArena Text: medicine and healthcare | Not measured | 1381 | Only Mistral Medium 3 measured |
| LMArena Text: legal and government | Not measured | 1384 | Only Mistral Medium 3 measured |
| LMArena Text: business and finance | Not measured | 1352 | Only Mistral Medium 3 measured |
| Neither model has a result on the other 7 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index14
| Benchmark | Kimi K2 0711 | Mistral Medium 3 | Leader |
|---|---|---|---|
| Design Arena: websites | 1050 | 1079 | Mistral Medium 3 |
| Design Arena: UI components | 1030 | 1024 | Kimi K2 0711 |
| Design Arena: game dev | 974 | 1018 | Mistral Medium 3 |
| Design Arena: data viz | 1018 | 1034 | Mistral Medium 3 |
| Design Arena: 3D | Not measured | 1083 | Only Mistral Medium 3 measured |
| Design Arena: all code categories | 1033 | 1069 | Mistral Medium 3 |
| Neither model has a result on the other 3 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Kimi K2 0711 | Mistral Medium 3 | Leader |
|---|---|---|---|
| IFBench | 41.5% | 39.3% | Kimi K2 0711 |
| Long context reasoning (AA-LCR) | 53.0% | 31.3% | Kimi K2 0711 |
| DTBench | Not measured | 62.3% | Only Mistral Medium 3 measured |
| Fiction.LiveBench | 61.1% | Not measured | Only Kimi K2 0711 measured |
| Creative writing (Lech Mazur) | 85.6% | Not measured | Only Kimi K2 0711 measured |
| CL-bench | 11.9% | Not measured | Only Kimi K2 0711 measured |
| LMArena Text | Not measured | 1370 | Only Mistral Medium 3 measured |
| LMArena Text: instruction following | Not measured | 1338 | Only Mistral Medium 3 measured |
| LMArena Text: creative writing | Not measured | 1343 | Only Mistral Medium 3 measured |
| LMArena Vision | Not measured | 1157 | Only Mistral Medium 3 measured |
| LMArena Text: English | Not measured | 1385 | Only Mistral Medium 3 measured |
| LMArena Text: non-English | Not measured | 1353 | Only Mistral Medium 3 measured |
| LMArena Text: Chinese | Not measured | 1374 | Only Mistral Medium 3 measured |
| LMArena Text: German | Not measured | 1377 | Only Mistral Medium 3 measured |
| LMArena Text: Japanese | Not measured | 1316 | Only Mistral Medium 3 measured |
| LMArena Text: Korean | Not measured | 1304 | Only Mistral Medium 3 measured |
| LMArena Text: French | Not measured | 1368 | Only Mistral Medium 3 measured |
| LMArena Text: Spanish | Not measured | 1364 | Only Mistral Medium 3 measured |
| LMArena Text: Russian | Not measured | 1359 | Only Mistral Medium 3 measured |
| LMArena Text: Polish | Not measured | 1371 | Only Mistral Medium 3 measured |
| LMArena Text: multi-turn | Not measured | 1384 | Only Mistral Medium 3 measured |
| LMArena Text: longer queries | Not measured | 1360 | Only Mistral Medium 3 measured |
| LMArena Text: writing and language | Not measured | 1352 | Only Mistral Medium 3 measured |
| LMArena Text: entertainment and media | Not measured | 1335 | Only Mistral Medium 3 measured |
| LMArena Vision: English | Not measured | 1172 | Only Mistral Medium 3 measured |
| LMArena Vision: Chinese | Not measured | 1161 | Only Mistral Medium 3 measured |
| LMArena Vision: reading text | Not measured | 1154 | Only Mistral Medium 3 measured |
| LMArena Vision: humor | Not measured | 1145 | Only Mistral Medium 3 measured |
| LMArena Vision: captioning | Not measured | 1094 | Only Mistral Medium 3 measured |
| LMArena Vision: recognizing things | Not measured | 1141 | Only Mistral Medium 3 measured |
| LMArena Vision: creative writing | Not measured | 1146 | Only Mistral Medium 3 measured |
| Neither model has a result on the other 15 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Kimi K2 0711 | Mistral Medium 3 | Leader |
|---|---|---|---|
| Neither model has a result on 5 boards here | |||
What each workload costs
Three fixed token mixes at each model's listed price, so per-token rates become a bill.
Chat turn
1K input + 500 output tokens
Mistral Medium 3 costs less
Repository review
50K input + 3K output tokens
Mistral Medium 3 costs less
Agent loop
200K input + 10K output tokens
Mistral Medium 3 costs less
Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.
Specification differences
The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.
| Specification | MoonshotAI Kimi K2 0711 | Mistral Medium 3 |
|---|---|---|
| Maker | Moonshot AI | Mistral AI |
| Weights | Open weights | No public weights listed |
| Released | July 11, 2025 | May 7, 2025 |
| Context window | 131K | 131K |
| Input $/Mtok | $0.57 | $0.40 |
| Output $/Mtok | $2.30 | $2.00 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 0 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Kimi K2 0711 better than Mistral Medium 3 for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Kimi K2 0711 has the edge where what matters is Design Arena: websites or Design Arena: game dev, where it leads.
Which is cheaper, Kimi K2 0711 or Mistral Medium 3?
Kimi K2 0711 costs $0.57 per million input tokens and $2.30 per million output tokens; Mistral Medium 3 costs $0.40 and $2.00. Cost per solved task is known for neither of them.
Which has the bigger context window, Kimi K2 0711 or Mistral Medium 3?
Neither: both take 131K tokens.
How many benchmarks is the Kimi K2 0711 vs Mistral Medium 3 comparison based on?
17 benchmarks have a result for both models as of October 21, 2026. Kimi K2 0711's coding index rests on 0 independent benchmarks and Mistral Medium 3's on 0. Where only one model has a result, the page says so instead of naming a winner.