Mistral Large 4 vs Qwen3 14B
Mistral Large 4 leads Qwen3 14B on the Artificial Analysis Intelligence Index, 38.4 to 6.7, and Qwen3 14B costs 18.2x less per output token ($0.23 vs $4.18 per million). Updated October 21, 2026; 9 benchmarks have a result for both.
Mistral Large 4 or Qwen3 14B: which to pick
Only Mistral Large 4 has a coding score, 56.4 on the Vibe Coding Index; Qwen3 14B has none, so the two cannot be ranked on coding.
Pick Qwen3 14B for output tokens 18.2x cheaper ($0.23 vs $4.18 per million).
- Shared results
- 9
- Mistral Large 4 only
- 72
- Qwen3 14B only
- 11
- Like-for-like categories
- 5 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
Only Mistral Large 4 has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
Mistral Large 4
Mistral Large 4 leads, 38.4 against 6.7.
Same board, both measured
Web design
Design Arena: websites
No call
Only Mistral Large 4 has a Design Arena: websites result, 1258.
Directional only
Long documents
Listed context window
Mistral Large 4
Mistral Large 4 takes 1.05M tokens against 41K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen3 14B
Mistral Large 4 $0.0034, Qwen3 14B $0.0002 per turn.
List prices
At a glance
- Coding index
- Mistral Large 4 56.4 from 5 benchmarks, Qwen3 14B not benchmarked.
- Widest category
- General, 41.1 points apart on average over 3 shared benchmarks.
- Widest single gap
- Long context reasoning (AA-LCR): Mistral Large 4 81.3% against Qwen3 14B 0.0%, 81.3 points apart on a 0 to 100 scale.
- Output price
- Mistral Large 4 $4.18 against Qwen3 14B $0.23 per million output tokens, 18.2x apart.
- Context window
- Mistral Large 4 takes 1.05M 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 Large 4 | Bars | Qwen3 14B | Ties |
|---|---|---|---|---|
| Coding | 1 | 0 | ||
| Intelligence | 2 | 0 | ||
| Reasoning | 2 | 0 | ||
| Math | 1 | 0 | ||
| General | 3 | 0 | ||
| All shared boards | 9 | 0 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index10
| Benchmark | Mistral Large 4 | Qwen3 14B | Leader |
|---|---|---|---|
| LiveBench coding | 60.0% | Not measured | Only Mistral Large 4 measured |
| LMArena WebDev | 1543 | Not measured | Only Mistral Large 4 measured |
| Terminal-Bench 4 (Vals AI) | 27.8% | Not measured | Only Mistral Large 4 measured |
| Vibe Code Bench (Vals AI) | 78.4% | Not measured | Only Mistral Large 4 measured |
| Code migration (Vals AI) | 30.6% | Not measured | Only Mistral Large 4 measured |
| IOI (Vals AI) | 45.3% | Not measured | Only Mistral Large 4 measured |
| SWE-bench Multimodal (Vals AI) | 33.1% | Not measured | Only Mistral Large 4 measured |
| Vibe Code Bench 1-100 (Vals AI) | 14.3% | Not measured | Only Mistral Large 4 measured |
| LiveCodeBench (Artificial Analysis run) | Not measured | 52.3% | Only Qwen3 14B measured |
| SciCode | 54.2% | 30.7% | Mistral Large 4 |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 5.3% | Only Qwen3 14B measured |
| FrontierCode | 39.4% | Not measured | Only Mistral Large 4 measured |
| ALE-Bench | 1213.2 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: coding | 1478 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: software and IT | 1467 | Not measured | Only Mistral Large 4 measured |
| LMArena WebDev: React | 1559 | Not measured | Only Mistral Large 4 measured |
| LMArena WebDev: HTML | 1487 | Not measured | Only Mistral Large 4 measured |
| Neither model has a result on the other 22 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Mistral Large 4 | Qwen3 14B | Leader |
|---|---|---|---|
| AA Intelligence Index | 38.4 | 6.7 | Mistral Large 4 |
| Epoch Capabilities Index | 150.0 | 138.2 | Mistral Large 4 |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index11 boards, none shared
| Benchmark | Mistral Large 4 | Qwen3 14B | Leader |
|---|---|---|---|
| LiveBench research | 28.1% | Not measured | Only Mistral Large 4 measured |
| LiveBench browser | 8.0% | Not measured | Only Mistral Large 4 measured |
| LiveBench long agentic | 11.8% | Not measured | Only Mistral Large 4 measured |
| Finance Agent (Vals AI) | 54.7% | Not measured | Only Mistral Large 4 measured |
| Tax Agent Bench (Vals AI) | 30.4% | Not measured | Only Mistral Large 4 measured |
| Legal Research Bench (Vals AI) | 31.7% | Not measured | Only Mistral Large 4 measured |
| Harvey's Legal Agent Benchmark (Vals AI) | 17.5% | Not measured | Only Mistral Large 4 measured |
| Excel Modeling Benchmark (Vals AI) | 56.2% | Not measured | Only Mistral Large 4 measured |
| BioMysteryBench (Vals AI) | 67.0% | Not measured | Only Mistral Large 4 measured |
| τ²-Bench Telecom | Not measured | 34.5% | Only Qwen3 14B measured |
| Berkeley Function Calling Leaderboard (BFCL) | Not measured | 41.0% | Only Qwen3 14B measured |
| Neither model has a result on the other 30 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Mistral Large 4 | Qwen3 14B | Leader |
|---|---|---|---|
| LiveBench reasoning | 83.9% | Not measured | Only Mistral Large 4 measured |
| MysteryMechanism (Vals AI) | 12.2% | Not measured | Only Mistral Large 4 measured |
| GPQA Diamond (Artificial Analysis run) | Not measured | 60.4% | Only Qwen3 14B measured |
| Humanity's Last Exam (Artificial Analysis run) | 35.0% | 4.5% | Mistral Large 4 |
| GPQA Diamond (Epoch AI run) | 88.1% | 63.8% | Mistral Large 4 |
| Chess puzzles | 33.0% | Not measured | Only Mistral Large 4 measured |
| Mystery game puzzles | 17.0% | Not measured | Only Mistral Large 4 measured |
| LMArena Text: hard prompts | 1444 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: expert | 1444 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: hard prompts in English | 1442 | Not measured | Only Mistral Large 4 measured |
| LMArena Vision: diagrams | 1288 | Not measured | Only Mistral Large 4 measured |
| Kagi LLM Benchmark | Not measured | 49.1% | Only Qwen3 14B measured |
| Neither model has a result on the other 10 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Mistral Large 4 | Qwen3 14B | Leader |
|---|---|---|---|
| AA Math Index | Not measured | 58.0 | Only Qwen3 14B measured |
| AIME 2025 (Artificial Analysis run) | Not measured | 58.0% | Only Qwen3 14B measured |
| OTIS Mock AIME | 98.3% | 66.4% | Mistral Large 4 |
| FrontierMath, tiers 1 to 3 | 58.6% | Not measured | Only Mistral Large 4 measured |
| FrontierMath, tier 4 | 26.8% | Not measured | Only Mistral Large 4 measured |
| ProofBench | 10.0% | Not measured | Only Mistral Large 4 measured |
| LMArena Text: math | 1469 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: mathematical work | 1462 | Not measured | Only Mistral Large 4 measured |
| Neither model has a result on the other 5 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
| Benchmark | Mistral Large 4 | Qwen3 14B | Leader |
|---|---|---|---|
| MedCode (Vals AI) | 40.7% | Not measured | Only Mistral Large 4 measured |
| MMLU Pro (Artificial Analysis run) | Not measured | 77.4% | Only Qwen3 14B measured |
| SimpleQA Verified | 20.0% | Not measured | Only Mistral Large 4 measured |
| LMArena Text: science | 1448 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: medicine and healthcare | 1433 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: legal and government | 1425 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: business and finance | 1439 | Not measured | Only Mistral Large 4 measured |
| Neither model has a result on the other 11 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index9 boards, none shared
| Benchmark | Mistral Large 4 | Qwen3 14B | Leader |
|---|---|---|---|
| Design Arena: websites | 1258 | Not measured | Only Mistral Large 4 measured |
| Design Arena: UI components | 1275 | Not measured | Only Mistral Large 4 measured |
| Design Arena: game dev | 1226 | Not measured | Only Mistral Large 4 measured |
| Design Arena: data viz | 1274 | Not measured | Only Mistral Large 4 measured |
| Design Arena: 3D | 1253 | Not measured | Only Mistral Large 4 measured |
| Design Arena: all code categories | 1259 | Not measured | Only Mistral Large 4 measured |
| Design Arena: SVG | 1233 | Not measured | Only Mistral Large 4 measured |
| Design Arena: ASCII art | 1202 | Not measured | Only Mistral Large 4 measured |
| LiveBench design | 65.6% | Not measured | Only Mistral Large 4 measured |
GeneralLike-for-likePublic boards, shown as published, kept out of the index30
| Benchmark | Mistral Large 4 | Qwen3 14B | Leader |
|---|---|---|---|
| LiveBench data analysis | 76.5% | Not measured | Only Mistral Large 4 measured |
| MedScribe (Vals AI) | 80.4% | Not measured | Only Mistral Large 4 measured |
| IFBench | Not measured | 40.5% | Only Qwen3 14B measured |
| Long context reasoning (AA-LCR) | 81.3% | 0.0% | Mistral Large 4 |
| DTBench | 88.2% | 64.0% | Mistral Large 4 |
| LMCA | 35.8% | 18.2% | Mistral Large 4 |
| Fiction.LiveBench | Not measured | 62.5% | Only Qwen3 14B measured |
| Surface Evolver Bench | 28.1% | Not measured | Only Mistral Large 4 measured |
| Furniture assembly | 20.8% | Not measured | Only Mistral Large 4 measured |
| LMArena Text | 1431 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: instruction following | 1422 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: creative writing | 1363 | Not measured | Only Mistral Large 4 measured |
| LMArena Vision | 1272 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: English | 1433 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: non-English | 1422 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: Chinese | 1492 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: Japanese | 1415 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: French | 1492 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: Spanish | 1455 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: Russian | 1417 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: multi-turn | 1435 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: longer queries | 1428 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: writing and language | 1386 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: entertainment and media | 1378 | Not measured | Only Mistral Large 4 measured |
| LMArena Vision: English | 1283 | Not measured | Only Mistral Large 4 measured |
| LMArena Vision: reading text | 1284 | Not measured | Only Mistral Large 4 measured |
| Neither model has a result on the other 20 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Mistral Large 4 | 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 Large 4 | Qwen3 14B |
|---|---|---|
| Maker | Mistral AI | Qwen |
| Weights | No public weights listed | Open weights |
| Released | October 6, 2026 | April 28, 2025 |
| Context window | 1.05M | 41K |
| Input $/Mtok | $1.36 | $0.11 |
| Output $/Mtok | $4.18 | $0.23 |
| Coding index | 56.4 | Not benchmarked |
| Independent measurements behind it | 5 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Mistral Large 4 better than Qwen3 14B for coding?
Only Mistral Large 4 has a coding score, 56.4 on the Vibe Coding Index; Qwen3 14B has none, so the two cannot be ranked on coding. Pick Qwen3 14B for output tokens 18.2x cheaper ($0.23 vs $4.18 per million).
Which is cheaper, Mistral Large 4 or Qwen3 14B?
Mistral Large 4 costs $1.36 per million input tokens and $4.18 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 Large 4 or Qwen3 14B?
Mistral Large 4, with 1.05M tokens against 41K.
How many benchmarks is the Mistral Large 4 vs Qwen3 14B comparison based on?
9 benchmarks have a result for both models as of October 21, 2026. Mistral Large 4's coding index rests on 5 independent benchmarks and Qwen3 14B's on 0. Where only one model has a result, the page says so instead of naming a winner.