Mistral Medium 3.1 vs Qwen3 14B
Mistral Medium 3.1 leads Qwen3 14B on the Artificial Analysis Intelligence Index, 9.2 to 6.7, and Qwen3 14B costs 8.7x less per output token ($0.23 vs $2.00 per million). Updated October 21, 2026; 14 benchmarks have a result for both.
Mistral Medium 3.1 or Qwen3 14B: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick Mistral Medium 3.1 for a larger context window (131K against 41K tokens) and work measured by LiveCodeBench (Artificial Analysis run) or GPQA Diamond (Artificial Analysis run), where it leads.
- Shared results
- 14
- Mistral Medium 3.1 only
- 60
- Qwen3 14B only
- 6
- Like-for-like categories
- 7 of 9
Only benchmarks that tested both models count toward a pick; a result only one model has is shown but not compared.
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
Mistral Medium 3.1
Mistral Medium 3.1 leads, 9.2 against 6.7.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only Mistral Medium 3.1 has a AA Agentic Index result, 1.9.
Directional only
Math
AIME
No call
Only Mistral Medium 3.1 has a AIME result, 42.3%.
Directional only
Knowledge
MMLU Pro
No call
Only Mistral Medium 3.1 has a MMLU Pro result, 75.3%.
Directional only
Web design
Design Arena: websites
No call
Only Mistral Medium 3.1 has a Design Arena: websites result, 1133.
Directional only
Long documents
Listed context window
Mistral Medium 3.1
Mistral Medium 3.1 takes 131K tokens against 41K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen3 14B
Mistral Medium 3.1 $0.0014, Qwen3 14B $0.0002 per turn.
List prices
At a glance
- Coding index
- Mistral Medium 3.1 not benchmarked, Qwen3 14B not benchmarked.
- Widest category
- Math, 19.7 points apart on average over 2 shared benchmarks.
- Widest single gap
- Long context reasoning (AA-LCR): Mistral Medium 3.1 42.7% against Qwen3 14B 0.0%, 42.7 points apart on a 0 to 100 scale.
- Output price
- Mistral Medium 3.1 $2.00 against Qwen3 14B $0.23 per million output tokens, 8.7x apart.
- Context window
- Mistral Medium 3.1 takes 131K tokens, Qwen3 14B 41K.
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 | Mistral Medium 3.1 | Bars | Qwen3 14B | Ties |
|---|---|---|---|---|
| Coding | 2 | 1 | ||
| Intelligence | 1 | 0 | ||
| Agentic work | 1 | 0 | ||
| Reasoning | 1 | 1 | ||
| Math | 0 | 2 | ||
| Knowledge | 0 | 1 | ||
| General | 3 | 1 | ||
| All shared boards | 8 | 6 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index21
| Benchmark | Mistral Medium 3.1 | Qwen3 14B | Leader |
|---|---|---|---|
| AA Coding Index | 20.5 | Not measured | Only Mistral Medium 3.1 measured |
| LiveCodeBench (Vals AI) | 44.8% | Not measured | Only Mistral Medium 3.1 measured |
| LiveCodeBench (Artificial Analysis run) | 40.6% | 52.3% | Qwen3 14B |
| SciCode | 32.4% | 30.7% | Mistral Medium 3.1 |
| Terminal-Bench Hard (Artificial Analysis run) | 10.6% | 5.3% | Mistral Medium 3.1 |
| ALE-Bench | 210.2 | Not measured | Only Mistral Medium 3.1 measured |
| LMArena Text: coding | 1433 | Not measured | Only Mistral Medium 3.1 measured |
| LMArena Text: software and IT | 1436 | Not measured | Only Mistral Medium 3.1 measured |
| Neither model has a result on the other 31 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Mistral Medium 3.1 | Qwen3 14B | Leader |
|---|---|---|---|
| AA Intelligence Index | 9.2 | 6.7 | Mistral Medium 3.1 |
| Epoch Capabilities Index | Not measured | 138.2 | Only Qwen3 14B measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Mistral Medium 3.1 | Qwen3 14B | Leader |
|---|---|---|---|
| AA Agentic Index | 1.9 | Not measured | Only Mistral Medium 3.1 measured |
| τ²-Bench Telecom | 40.6% | 34.5% | Mistral Medium 3.1 |
| Berkeley Function Calling Leaderboard (BFCL) | Not measured | 41.0% | Only Qwen3 14B measured |
| Neither model has a result on the other 38 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index11
| Benchmark | Mistral Medium 3.1 | Qwen3 14B | Leader |
|---|---|---|---|
| MMMU Pro (Vals AI) | 63.0% | Not measured | Only Mistral Medium 3.1 measured |
| GPQA Diamond (Artificial Analysis run) | 58.8% | 60.4% | Qwen3 14B |
| Humanity's Last Exam (Artificial Analysis run) | 4.7% | 4.5% | Mistral Medium 3.1 |
| GPQA Diamond (Epoch AI run) | Not measured | 63.8% | Only Qwen3 14B measured |
| LMArena Text: hard prompts | 1426 | Not measured | Only Mistral Medium 3.1 measured |
| LMArena Text: expert | 1408 | Not measured | Only Mistral Medium 3.1 measured |
| LMArena Text: hard prompts in English | 1435 | Not measured | Only Mistral Medium 3.1 measured |
| LMArena Vision: diagrams | 1175 | Not measured | Only Mistral Medium 3.1 measured |
| LMArena Vision: homework | 1165 | Not measured | Only Mistral Medium 3.1 measured |
| Kagi LLM Benchmark | Not measured | 49.1% | Only Qwen3 14B measured |
| Neither model has a result on the other 12 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Mistral Medium 3.1 | Qwen3 14B | Leader |
|---|---|---|---|
| AIME | 42.3% | Not measured | Only Mistral Medium 3.1 measured |
| MATH 500 (Vals AI) | 87.0% | Not measured | Only Mistral Medium 3.1 measured |
| MGSM (Vals AI) | 90.9% | Not measured | Only Mistral Medium 3.1 measured |
| AA Math Index | 38.3 | 58.0 | Qwen3 14B |
| AIME 2025 (Artificial Analysis run) | 38.3% | 58.0% | Qwen3 14B |
| OTIS Mock AIME | Not measured | 66.4% | Only Qwen3 14B measured |
| LMArena Text: math | 1408 | Not measured | Only Mistral Medium 3.1 measured |
| LMArena Text: mathematical work | 1412 | Not measured | Only Mistral Medium 3.1 measured |
| Neither model has a result on the other 5 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Mistral Medium 3.1 | Qwen3 14B | Leader |
|---|---|---|---|
| MMLU Pro | 75.3% | Not measured | Only Mistral Medium 3.1 measured |
| LegalBench (Vals AI) | 62.0% | Not measured | Only Mistral Medium 3.1 measured |
| CorpFin (Vals AI) | 50.7% | Not measured | Only Mistral Medium 3.1 measured |
| TaxEval (Vals AI) | 70.3% | Not measured | Only Mistral Medium 3.1 measured |
| MortgageTax (Vals AI) | 36.5% | Not measured | Only Mistral Medium 3.1 measured |
| MedQA (Vals AI) | 78.2% | Not measured | Only Mistral Medium 3.1 measured |
| MMLU Pro (Artificial Analysis run) | 68.3% | 77.4% | Qwen3 14B |
| LMArena Text: science | 1444 | Not measured | Only Mistral Medium 3.1 measured |
| LMArena Text: medicine and healthcare | 1449 | Not measured | Only Mistral Medium 3.1 measured |
| LMArena Text: legal and government | 1439 | Not measured | Only Mistral Medium 3.1 measured |
| LMArena Text: business and finance | 1418 | Not measured | Only Mistral Medium 3.1 measured |
| Neither model has a result on the other 7 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | Mistral Medium 3.1 | Qwen3 14B | Leader |
|---|---|---|---|
| Design Arena: websites | 1133 | Not measured | Only Mistral Medium 3.1 measured |
| Design Arena: UI components | 1100 | Not measured | Only Mistral Medium 3.1 measured |
| Design Arena: game dev | 1074 | Not measured | Only Mistral Medium 3.1 measured |
| Design Arena: data viz | 1144 | Not measured | Only Mistral Medium 3.1 measured |
| Design Arena: 3D | 1081 | Not measured | Only Mistral Medium 3.1 measured |
| Design Arena: all code categories | 1120 | Not measured | Only Mistral Medium 3.1 measured |
| Design Arena: SVG | 993 | Not measured | Only Mistral Medium 3.1 measured |
| Design Arena: ASCII art | 997 | Not measured | Only Mistral Medium 3.1 measured |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index31
| Benchmark | Mistral Medium 3.1 | Qwen3 14B | Leader |
|---|---|---|---|
| IFBench | 39.8% | 40.5% | Qwen3 14B |
| Long context reasoning (AA-LCR) | 42.7% | 0.0% | Mistral Medium 3.1 |
| DTBench | 67.5% | 64.0% | Mistral Medium 3.1 |
| LMCA | 19.1% | 18.2% | Mistral Medium 3.1 |
| Fiction.LiveBench | Not measured | 62.5% | Only Qwen3 14B measured |
| LMArena Text | 1424 | Not measured | Only Mistral Medium 3.1 measured |
| LMArena Text: instruction following | 1398 | Not measured | Only Mistral Medium 3.1 measured |
| LMArena Text: creative writing | 1391 | Not measured | Only Mistral Medium 3.1 measured |
| LMArena Vision | 1172 | Not measured | Only Mistral Medium 3.1 measured |
| LMArena Text: English | 1438 | Not measured | Only Mistral Medium 3.1 measured |
| LMArena Text: non-English | 1408 | Not measured | Only Mistral Medium 3.1 measured |
| LMArena Text: Chinese | 1447 | Not measured | Only Mistral Medium 3.1 measured |
| LMArena Text: German | 1432 | Not measured | Only Mistral Medium 3.1 measured |
| LMArena Text: Japanese | 1379 | Not measured | Only Mistral Medium 3.1 measured |
| LMArena Text: Korean | 1380 | Not measured | Only Mistral Medium 3.1 measured |
| LMArena Text: French | 1460 | Not measured | Only Mistral Medium 3.1 measured |
| LMArena Text: Spanish | 1433 | Not measured | Only Mistral Medium 3.1 measured |
| LMArena Text: Russian | 1411 | Not measured | Only Mistral Medium 3.1 measured |
| LMArena Text: Polish | 1430 | Not measured | Only Mistral Medium 3.1 measured |
| LMArena Text: multi-turn | 1418 | Not measured | Only Mistral Medium 3.1 measured |
| LMArena Text: longer queries | 1406 | Not measured | Only Mistral Medium 3.1 measured |
| LMArena Text: writing and language | 1395 | Not measured | Only Mistral Medium 3.1 measured |
| LMArena Text: entertainment and media | 1390 | Not measured | Only Mistral Medium 3.1 measured |
| LMArena Vision: English | 1179 | Not measured | Only Mistral Medium 3.1 measured |
| LMArena Vision: Chinese | 1190 | Not measured | Only Mistral Medium 3.1 measured |
| LMArena Vision: reading text | 1175 | Not measured | Only Mistral Medium 3.1 measured |
| LMArena Vision: humor | 1168 | Not measured | Only Mistral Medium 3.1 measured |
| LMArena Vision: captioning | 1145 | Not measured | Only Mistral Medium 3.1 measured |
| LMArena Vision: recognizing things | 1147 | Not measured | Only Mistral Medium 3.1 measured |
| LMArena Vision: creative writing | 1200 | Not measured | Only Mistral Medium 3.1 measured |
| Neither model has a result on the other 16 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Mistral Medium 3.1 | Qwen3 14B | 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
Qwen3 14B costs less
Repository review
50K input + 3K output tokens
Qwen3 14B costs less
Agent loop
200K input + 10K output tokens
Qwen3 14B 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 | Mistral Medium 3.1 | Qwen3 14B |
|---|---|---|
| Maker | Mistral AI | Qwen |
| Weights | No public weights listed | Open weights |
| Released | August 13, 2025 | April 28, 2025 |
| Context window | 131K | 41K |
| Input $/Mtok | $0.40 | $0.11 |
| Output $/Mtok | $2.00 | $0.23 |
| 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 Mistral Medium 3.1 better than Qwen3 14B for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Mistral Medium 3.1 for a larger context window (131K against 41K tokens) and work measured by LiveCodeBench (Artificial Analysis run) or GPQA Diamond (Artificial Analysis run), where it leads.
Which is cheaper, Mistral Medium 3.1 or Qwen3 14B?
Mistral Medium 3.1 costs $0.40 per million input tokens and $2.00 per million output tokens; Qwen3 14B costs $0.11 and $0.23. Cost per solved task is known for neither of them.
Which has the bigger context window, Mistral Medium 3.1 or Qwen3 14B?
Mistral Medium 3.1, with 131K tokens against 41K.
How many benchmarks is the Mistral Medium 3.1 vs Qwen3 14B comparison based on?
14 benchmarks have a result for both models as of October 21, 2026. Mistral Medium 3.1's coding index rests on 0 independent benchmarks and Qwen3 14B's on 0. Where only one model has a result, the page says so instead of naming a winner.