Mistral Large 4 vs Hy3
Updated October 21, 2026. 40 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
Pick Mistral Large 4 for coding: it scores 55.3 on the Vibe Coding Index against 43.9 for Hy3.
Pick Hy3 when output tokens cost 7.9x less, or when what matters is LMArena Text: hard prompts or LMArena Text: expert, where it leads.
- Shared results
- 40
- Mistral Large 4 only
- 41
- Hy3 only
- 4
- Like-for-like categories
- 6 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, four public coding benchmarks
Mistral Large 4
Mistral Large 4 scores 55.3 against 43.9.
2 and 1 benchmarks behind the scores
Intelligence
AA Intelligence Index
No call
Only Mistral Large 4 has a AA Intelligence Index result, 38.4.
Directional only
Web design
Design Arena: websites
Mistral Large 4
Mistral Large 4 leads, 1258 against 1230.
Same board, both measured
Long documents
Listed context window
Mistral Large 4
Mistral Large 4 takes 1.05M tokens against 262K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Hy3
Mistral Large 4 $0.0034, Hy3 $0.0004 per turn.
List prices
At a glance
- Coding index
- Mistral Large 4 55.3 from 2 benchmarks, Hy3 43.9 from 1 benchmark.
- Widest category
- Web design, 5.6 points apart on average over 8 shared benchmarks.
- Widest single gap
- Design Arena: data viz: Mistral Large 4 1274 against Hy3 1163, 13.9 points apart on a 0 to 100 scale.
- Output price
- Mistral Large 4 $4.18 against Hy3 $0.528 per million output tokens, 7.9x apart.
- Context window
- Mistral Large 4 takes 1.05M tokens, Hy3 262K.
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 | Hy3 | Ties |
|---|---|---|---|---|
| Coding | 7 | 0 | ||
| Reasoning | 1 | 3 | ||
| Math | 0 | 2 | ||
| Knowledge | 2 | 2 | ||
| Web design | 8 | 0 | ||
| General | 4 | 11 | ||
| All shared boards | 22 | 18 |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index70
| Benchmark | Mistral Large 4 | Hy3 | Leader |
|---|---|---|---|
| LiveBench coding | 60.0% | Not measured | Only Mistral Large 4 measured |
| LMArena WebDev | 1543 | 1507 | Mistral Large 4 |
| 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 |
| SciCode | 54.2% | 48.6% | Mistral Large 4 |
| FrontierCode | 39.4% | Not measured | Only Mistral Large 4 measured |
| ALE-Bench | 1213.2 | 838.6 | Mistral Large 4 |
| LMArena Text: coding | 1478 | 1466 | Mistral Large 4 |
| LMArena Text: software and IT | 1467 | 1463 | Mistral Large 4 |
| LMArena WebDev: React | 1559 | 1511 | Mistral Large 4 |
| LMArena WebDev: HTML | 1487 | 1487 | Mistral Large 4 |
| Neither model has a result on the other 23 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | Mistral Large 4 | Hy3 | Leader |
|---|---|---|---|
| AA Intelligence Index | 38.4 | Not measured | Only Mistral Large 4 measured |
| Epoch Capabilities Index | 150.0 | Not measured | Only Mistral Large 4 measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index9 boards, none shared
| Benchmark | Mistral Large 4 | Hy3 | 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 |
| Neither model has a result on the other 30 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index13
| Benchmark | Mistral Large 4 | Hy3 | 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 | 89.7% | Only Hy3 measured |
| Humanity's Last Exam (Artificial Analysis run) | 35.0% | 33.5% | Mistral Large 4 |
| GPQA Diamond (Epoch AI run) | 88.1% | Not measured | Only Mistral Large 4 measured |
| 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 | 1447 | Hy3 |
| LMArena Text: expert | 1444 | 1461 | Hy3 |
| LMArena Text: hard prompts in English | 1442 | 1455 | Hy3 |
| LMArena Vision: diagrams | 1288 | Not measured | Only Mistral Large 4 measured |
| Neither model has a result on the other 10 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Mistral Large 4 | Hy3 | Leader |
|---|---|---|---|
| OTIS Mock AIME | 98.3% | Not measured | Only Mistral Large 4 measured |
| 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 | 1473 | Hy3 |
| LMArena Text: mathematical work | 1462 | 1482 | Hy3 |
| Neither model has a result on the other 7 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index22
| Benchmark | Mistral Large 4 | Hy3 | Leader |
|---|---|---|---|
| MedCode (Vals AI) | 40.7% | Not measured | Only Mistral Large 4 measured |
| SimpleQA Verified | 20.0% | Not measured | Only Mistral Large 4 measured |
| LMArena Text: science | 1448 | 1457 | Hy3 |
| LMArena Text: medicine and healthcare | 1433 | 1452 | Hy3 |
| LMArena Text: legal and government | 1425 | 1422 | Mistral Large 4 |
| LMArena Text: business and finance | 1439 | 1424 | Mistral Large 4 |
| Neither model has a result on the other 11 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index80
| Benchmark | Mistral Large 4 | Hy3 | Leader |
|---|---|---|---|
| Design Arena: websites | 1258 | 1230 | Mistral Large 4 |
| Design Arena: UI components | 1275 | 1205 | Mistral Large 4 |
| Design Arena: game dev | 1226 | 1208 | Mistral Large 4 |
| Design Arena: data viz | 1274 | 1163 | Mistral Large 4 |
| Design Arena: 3D | 1253 | 1233 | Mistral Large 4 |
| Design Arena: all code categories | 1259 | 1227 | Mistral Large 4 |
| Design Arena: SVG | 1232 | 1199 | Mistral Large 4 |
| Design Arena: ASCII art | 1203 | 1157 | Mistral Large 4 |
| LiveBench design | 65.6% | Not measured | Only Mistral Large 4 measured |
GeneralLike-for-likePublic boards, shown as published, kept out of the index411
| Benchmark | Mistral Large 4 | Hy3 | 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 |
| Long context reasoning (AA-LCR) | 81.3% | 79.0% | Mistral Large 4 |
| DTBench | 88.2% | Not measured | Only Mistral Large 4 measured |
| LMCA | 35.8% | Not measured | Only Mistral Large 4 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 | 1438 | Hy3 |
| LMArena Text: instruction following | 1422 | 1426 | Hy3 |
| LMArena Text: creative writing | 1363 | 1403 | Hy3 |
| LMArena Vision | 1272 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: English | 1433 | 1448 | Hy3 |
| LMArena Text: non-English | 1422 | 1426 | Hy3 |
| LMArena Text: Chinese | 1492 | 1485 | Mistral Large 4 |
| LMArena Text: German | Not measured | 1449 | Only Hy3 measured |
| LMArena Text: Japanese | 1415 | 1397 | Mistral Large 4 |
| LMArena Text: Korean | Not measured | 1396 | Only Hy3 measured |
| LMArena Text: French | 1492 | 1456 | Mistral Large 4 |
| LMArena Text: Spanish | 1455 | 1457 | Hy3 |
| LMArena Text: Russian | 1417 | 1432 | Hy3 |
| LMArena Text: Polish | Not measured | 1447 | Only Hy3 measured |
| LMArena Text: multi-turn | 1435 | 1436 | Hy3 |
| LMArena Text: longer queries | 1428 | 1442 | Hy3 |
| LMArena Text: writing and language | 1386 | 1414 | Hy3 |
| LMArena Text: entertainment and media | 1378 | 1400 | Hy3 |
| 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 19 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Mistral Large 4 | Hy3 | 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
Hy3 costs less
Repository review
50K input + 3K output tokens
Hy3 costs less
Agent loop
200K input + 10K output tokens
Hy3 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 | Tencent Hy3 |
|---|---|---|
| Maker | Mistral AI | Tencent |
| Weights | No public weights listed | Open weights |
| Released | October 6, 2026 | July 6, 2026 |
| Context window | 1.05M | 262K |
| Input $/Mtok | $1.36 | $0.132 |
| Output $/Mtok | $4.18 | $0.528 |
| Coding index | 55.3 | 43.9 |
| Independent measurements behind it | 2 | 1 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Mistral Large 4 better than Hy3 for coding?
Pick Mistral Large 4 for coding: it scores 55.3 on the Vibe Coding Index against 43.9 for Hy3. Pick Hy3 when output tokens cost 7.9x less, or when what matters is LMArena Text: hard prompts or LMArena Text: expert, where it leads.
Which is cheaper, Mistral Large 4 or Hy3?
Mistral Large 4 costs $1.36 per million input tokens and $4.18 per million output tokens; Hy3 costs $0.132 and $0.528. Cost per solved task is known for neither of them.
Which has the bigger context window, Mistral Large 4 or Hy3?
Mistral Large 4, with 1.05M tokens against 262K.
How many benchmarks is the Mistral Large 4 vs Hy3 comparison based on?
40 benchmarks have a result for both models as of October 21, 2026. Mistral Large 4's coding index rests on 2 independent benchmarks and Hy3's on 1. Where only one model has a result, the page says so instead of naming a winner.