Mistral Medium 3.5 vs Hy4
Hy4 leads Mistral Medium 3.5 on coding, 65.2 to 25.4 on the Vibe Coding Index, and Hy4 costs 6.0x less per output token ($1.2505 vs $7.50 per million). Updated November 5, 2026; 3 benchmarks have a result for both.
Mistral Medium 3.5 or Hy4: which to pick
Pick Hy4 for coding: it scores 65.2 on the Vibe Coding Index against 25.4 for Mistral Medium 3.5, though on 2 benchmarks against 3.
Mistral Medium 3.5 is neither cheaper nor larger in context, and leads no benchmark both models were measured on.
- Shared results
- 3
- Mistral Medium 3.5 only
- 80
- Hy4 only
- 3
- Like-for-like categories
- 2 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
Hy4
Hy4 scores 65.2 against 25.4.
3 and 2 benchmarks behind the scores
Intelligence
AA Intelligence Index
No call
Only Mistral Medium 3.5 has a AA Intelligence Index result, 4.6.
Directional only
Agentic work
AA Agentic Index
No call
Only Mistral Medium 3.5 has a AA Agentic Index result, 7.0.
Directional only
Reasoning
GPQA Diamond
No call
Only Mistral Medium 3.5 has a GPQA Diamond result, 34.9%.
Directional only
Knowledge
MMLU Pro
No call
Only Mistral Medium 3.5 has a MMLU Pro result, 75.3%.
Directional only
Web design
Design Arena: websites
No call
Only Mistral Medium 3.5 has a Design Arena: websites result, 1141.
Directional only
General
Vals Index
No call
Only Hy4 has a Vals Index result, 59.4%.
Directional only
Long documents
Listed context window
Hy4
Hy4 takes 1.05M tokens against 262K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Hy4
Mistral Medium 3.5 $0.0053, Hy4 $0.0010 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Mistral Medium 3.5 has the number, $6.02.
Directional only
At a glance
- Coding index
- Mistral Medium 3.5 25.4 from 3 benchmarks, Hy4 65.2 from 2 benchmarks.
- Widest category
- Coding, 78.1 points apart on average over 1 shared benchmark.
- Widest single gap
- Vibe Code Bench (Vals AI): Mistral Medium 3.5 2.9% against Hy4 81.0%, 78.1 points apart on a 0 to 100 scale.
- Output price
- Mistral Medium 3.5 $7.50 against Hy4 $1.2505 per million output tokens, 6.0x apart.
- Context window
- Mistral Medium 3.5 takes 262K tokens, Hy4 1.05M.
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 3.5 | Bars | Hy4 | Ties |
|---|---|---|---|---|
| Coding | 0 | 1 | ||
| Agentic work | 0 | 2 | ||
| All shared boards | 0 | 3 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index01
| Benchmark | Mistral Medium 3.5 | Hy4 | Leader |
|---|---|---|---|
| LMArena WebDev | 1264 | Not measured | Only Mistral Medium 3.5 measured |
| AA Coding Index | 46.9 | Not measured | Only Mistral Medium 3.5 measured |
| SWE-bench Verified (Vals AI) | 66.4% | Not measured | Only Mistral Medium 3.5 measured |
| Terminal-Bench 4 (Vals AI) | Not measured | 39.4% | Only Hy4 measured |
| Vibe Code Bench (Vals AI) | 2.9% | 81.0% | Hy4 |
| Code migration (Vals AI) | 5.1% | Not measured | Only Mistral Medium 3.5 measured |
| Terminal-Bench 2.1 (Vals AI) | 39.0% | Not measured | Only Mistral Medium 3.5 measured |
| SciCode | 40.2% | Not measured | Only Mistral Medium 3.5 measured |
| Terminal-Bench Hard (Artificial Analysis run) | 33.3% | Not measured | Only Mistral Medium 3.5 measured |
| ALE-Bench | 764.0 | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Text: coding | 1460 | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Text: software and IT | 1458 | Not measured | Only Mistral Medium 3.5 measured |
| LMArena WebDev: React | 1254 | Not measured | Only Mistral Medium 3.5 measured |
| LMArena WebDev: HTML | 1308 | Not measured | Only Mistral Medium 3.5 measured |
| GameBench 2 | 27.0 | Not measured | Only Mistral Medium 3.5 measured |
| Neither model has a result on the other 35 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | Mistral Medium 3.5 | Hy4 | Leader |
|---|---|---|---|
| AA Intelligence Index | 4.6 | Not measured | Only Mistral Medium 3.5 measured |
| Epoch Capabilities Index | 141.6 | Not measured | Only Mistral Medium 3.5 measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Mistral Medium 3.5 | Hy4 | Leader |
|---|---|---|---|
| AA Agentic Index | 7.0 | Not measured | Only Mistral Medium 3.5 measured |
| Finance Agent (Vals AI) | 32.1% | Not measured | Only Mistral Medium 3.5 measured |
| Tax Agent Bench (Vals AI) | 4.5% | 34.4% | Hy4 |
| Legal Research Bench (Vals AI) | 9.1% | 41.4% | Hy4 |
| Harvey's Legal Agent Benchmark (Vals AI) | Not measured | 12.5% | Only Hy4 measured |
| Excel Modeling Benchmark (Vals AI) | 11.2% | Not measured | Only Mistral Medium 3.5 measured |
| τ²-Bench Telecom | 94.2% | Not measured | Only Mistral Medium 3.5 measured |
| Neither model has a result on the other 37 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index9 boards, none shared
| Benchmark | Mistral Medium 3.5 | Hy4 | Leader |
|---|---|---|---|
| GPQA Diamond | 34.9% | Not measured | Only Mistral Medium 3.5 measured |
| GPQA Diamond (Artificial Analysis run) | 74.8% | Not measured | Only Mistral Medium 3.5 measured |
| Humanity's Last Exam (Artificial Analysis run) | 13.8% | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Text: hard prompts | 1437 | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Text: expert | 1432 | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Text: hard prompts in English | 1445 | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Vision: diagrams | 1254 | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Vision: homework | 1230 | Not measured | Only Mistral Medium 3.5 measured |
| Kagi LLM Benchmark | 41.4% | Not measured | Only Mistral Medium 3.5 measured |
| Neither model has a result on the other 15 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
| Benchmark | Mistral Medium 3.5 | Hy4 | Leader |
|---|---|---|---|
| ProofBench | 9.0% | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Text: math | 1432 | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Text: mathematical work | 1441 | Not measured | Only Mistral Medium 3.5 measured |
| Neither model has a result on the other 11 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index10 boards, none shared
| Benchmark | Mistral Medium 3.5 | Hy4 | Leader |
|---|---|---|---|
| MMLU Pro | 75.3% | Not measured | Only Mistral Medium 3.5 measured |
| CaseLaw (Vals AI) | 44.2% | Not measured | Only Mistral Medium 3.5 measured |
| CorpFin (Vals AI) | 58.8% | Not measured | Only Mistral Medium 3.5 measured |
| TaxEval (Vals AI) | 68.0% | Not measured | Only Mistral Medium 3.5 measured |
| MortgageTax (Vals AI) | 28.9% | Not measured | Only Mistral Medium 3.5 measured |
| MedCode (Vals AI) | 33.8% | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Text: science | 1428 | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Text: medicine and healthcare | 1409 | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Text: legal and government | 1437 | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Text: business and finance | 1426 | Not measured | Only Mistral Medium 3.5 measured |
| Neither model has a result on the other 10 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | Mistral Medium 3.5 | Hy4 | Leader |
|---|---|---|---|
| Design Arena: websites | 1141 | Not measured | Only Mistral Medium 3.5 measured |
| Design Arena: UI components | 1074 | Not measured | Only Mistral Medium 3.5 measured |
| Design Arena: game dev | 1078 | Not measured | Only Mistral Medium 3.5 measured |
| Design Arena: data viz | 1121 | Not measured | Only Mistral Medium 3.5 measured |
| Design Arena: 3D | 1057 | Not measured | Only Mistral Medium 3.5 measured |
| Design Arena: all code categories | 1120 | Not measured | Only Mistral Medium 3.5 measured |
| Design Arena: SVG | 946 | Not measured | Only Mistral Medium 3.5 measured |
| Design Arena: ASCII art | 1059 | Not measured | Only Mistral Medium 3.5 measured |
| Neither model has a result on the other 1 board here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index32 boards, none shared
| Benchmark | Mistral Medium 3.5 | Hy4 | Leader |
|---|---|---|---|
| Vals Index | Not measured | 59.4% | Only Hy4 measured |
| SAGE (Vals AI) | 72.0% | Not measured | Only Mistral Medium 3.5 measured |
| MedScribe (Vals AI) | 67.7% | Not measured | Only Mistral Medium 3.5 measured |
| Vals Multimodal Index | 34.8% | Not measured | Only Mistral Medium 3.5 measured |
| IFBench | 68.8% | Not measured | Only Mistral Medium 3.5 measured |
| Long context reasoning (AA-LCR) | 69.3% | Not measured | Only Mistral Medium 3.5 measured |
| DTBench | 75.5% | Not measured | Only Mistral Medium 3.5 measured |
| LMCA | 26.1% | Not measured | Only Mistral Medium 3.5 measured |
| Surface Evolver Bench | 26.9% | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Text | 1421 | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Text: instruction following | 1415 | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Text: creative writing | 1374 | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Vision | 1222 | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Text: English | 1433 | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Text: non-English | 1405 | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Text: Chinese | 1445 | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Text: German | 1453 | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Text: Korean | 1384 | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Text: French | 1449 | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Text: Spanish | 1411 | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Text: Russian | 1396 | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Text: Polish | 1430 | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Text: multi-turn | 1423 | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Text: longer queries | 1415 | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Text: writing and language | 1384 | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Text: entertainment and media | 1382 | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Vision: English | 1240 | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Vision: Chinese | 1244 | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Vision: reading text | 1233 | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Vision: humor | 1216 | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Vision: creative writing | 1198 | Not measured | Only Mistral Medium 3.5 measured |
| EQ-Bench 4 | 983 | Not measured | Only Mistral Medium 3.5 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 3.5 | Hy4 | 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
Hy4 costs less
Repository review
50K input + 3K output tokens
Hy4 costs less
Agent loop
200K input + 10K output tokens
Hy4 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 3.5 | Tencent Hy4 |
|---|---|---|
| Maker | Mistral AI | Tencent |
| Weights | No public weights listed | Open weights |
| Released | April 30, 2026 | November 4, 2026 |
| Context window | 262K | 1.05M |
| Input $/Mtok | $1.50 | $0.417 |
| Output $/Mtok | $7.50 | $1.2505 |
| Coding index | 25.4 | 65.2 |
| Independent measurements behind it | 3 | 2 |
| Cost per solved task | $6.02 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Mistral Medium 3.5 better than Hy4 for coding?
Pick Hy4 for coding: it scores 65.2 on the Vibe Coding Index against 25.4 for Mistral Medium 3.5, though on 2 benchmarks against 3. Mistral Medium 3.5 is neither cheaper nor larger in context, and leads no benchmark both models were measured on.
Which is cheaper, Mistral Medium 3.5 or Hy4?
Mistral Medium 3.5 costs $1.50 per million input tokens and $7.50 per million output tokens; Hy4 costs $0.417 and $1.2505. Cost per solved task is known for Mistral Medium 3.5 only.
Which has the bigger context window, Mistral Medium 3.5 or Hy4?
Hy4, with 1.05M tokens against 262K.
How many benchmarks is the Mistral Medium 3.5 vs Hy4 comparison based on?
3 benchmarks have a result for both models as of November 5, 2026. Mistral Medium 3.5's coding index rests on 3 independent benchmarks and Hy4's on 2. Where only one model has a result, the page says so instead of naming a winner.