Mistral Medium 3.5 vs Hy3
Hy3 costs 14.2x less per output token than Mistral Medium 3.5 ($0.528 vs $7.50 per million). Updated October 22, 2026; 43 benchmarks have a result for both.
Mistral Medium 3.5 or Hy3: which to pick
Only Mistral Medium 3.5 has a coding score, 25.5 on the Vibe Coding Index; Hy3 has none, so the two cannot be ranked on coding.
Pick Hy3 for output tokens 14.2x cheaper ($0.528 vs $7.50 per million) and work measured by LMArena WebDev or SciCode, where it leads.
- Shared results
- 43
- Mistral Medium 3.5 only
- 38
- Hy3 only
- 1
- Like-for-like categories
- 6 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 Medium 3.5 has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
No call
Only Mistral Medium 3.5 has a AA Intelligence Index result, 14.2.
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
Hy3
Hy3 leads, 1230 against 1142.
Same board, both measured
Long documents
Listed context window
No call
Both take 262K tokens.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Hy3
Mistral Medium 3.5 $0.0053, Hy3 $0.0004 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 25.5 from 3 benchmarks, Hy3 not benchmarked.
- Widest category
- Coding, 17.1 points apart on average over 7 shared benchmarks.
- Widest single gap
- LMArena WebDev: React: Mistral Medium 3.5 1254 against Hy3 1511, 42.8 points apart on a 0 to 100 scale.
- Output price
- Mistral Medium 3.5 $7.50 against Hy3 $0.528 per million output tokens, 14.2x apart.
- Context window
- Both take 262K 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 | Mistral Medium 3.5 | Bars | Hy3 | Ties |
|---|---|---|---|---|
| Coding | 0 | 7 | ||
| Reasoning | 0 | 5 | ||
| Math | 0 | 2 | ||
| Knowledge | 2 | 2 | ||
| Web design | 0 | 8 | ||
| General | 1 | 16 | ||
| All shared boards | 3 | 40 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index07
| Benchmark | Mistral Medium 3.5 | Hy3 | Leader |
|---|---|---|---|
| LMArena WebDev | 1264 | 1507 | Hy3 |
| 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 |
| Vibe Code Bench (Vals AI) | 2.9% | Not measured | Only Mistral Medium 3.5 measured |
| 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% | 48.6% | Hy3 |
| Terminal-Bench Hard (Artificial Analysis run) | 33.3% | Not measured | Only Mistral Medium 3.5 measured |
| ALE-Bench | 764.0 | 838.6 | Hy3 |
| LMArena Text: coding | 1460 | 1466 | Hy3 |
| LMArena Text: software and IT | 1458 | 1463 | Hy3 |
| LMArena WebDev: React | 1254 | 1511 | Hy3 |
| LMArena WebDev: HTML | 1308 | 1487 | Hy3 |
| Neither model has a result on the other 26 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | Mistral Medium 3.5 | Hy3 | Leader |
|---|---|---|---|
| AA Intelligence Index | 14.2 | Not measured | Only Mistral Medium 3.5 measured |
| Epoch Capabilities Index | 141.4 | Not measured | Only Mistral Medium 3.5 measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | Mistral Medium 3.5 | Hy3 | 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% | Not measured | Only Mistral Medium 3.5 measured |
| Legal Research Bench (Vals AI) | 9.1% | Not measured | Only Mistral Medium 3.5 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 35 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index05
| Benchmark | Mistral Medium 3.5 | Hy3 | Leader |
|---|---|---|---|
| GPQA Diamond | 34.9% | Not measured | Only Mistral Medium 3.5 measured |
| GPQA Diamond (Artificial Analysis run) | 74.8% | 89.7% | Hy3 |
| Humanity's Last Exam (Artificial Analysis run) | 13.8% | 33.5% | Hy3 |
| LMArena Text: hard prompts | 1436 | 1447 | Hy3 |
| LMArena Text: expert | 1432 | 1461 | Hy3 |
| LMArena Text: hard prompts in English | 1445 | 1455 | Hy3 |
| 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 13 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Mistral Medium 3.5 | Hy3 | Leader |
|---|---|---|---|
| ProofBench | 9.0% | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Text: math | 1431 | 1473 | Hy3 |
| LMArena Text: mathematical work | 1440 | 1482 | Hy3 |
| Neither model has a result on the other 10 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index22
| Benchmark | Mistral Medium 3.5 | Hy3 | 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 | 1457 | Hy3 |
| LMArena Text: medicine and healthcare | 1409 | 1452 | Hy3 |
| LMArena Text: legal and government | 1437 | 1422 | Mistral Medium 3.5 |
| LMArena Text: business and finance | 1426 | 1424 | Mistral Medium 3.5 |
| Neither model has a result on the other 8 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index08
| Benchmark | Mistral Medium 3.5 | Hy3 | Leader |
|---|---|---|---|
| Design Arena: websites | 1142 | 1230 | Hy3 |
| Design Arena: UI components | 1076 | 1204 | Hy3 |
| Design Arena: game dev | 1079 | 1208 | Hy3 |
| Design Arena: data viz | 1120 | 1164 | Hy3 |
| Design Arena: 3D | 1060 | 1232 | Hy3 |
| Design Arena: all code categories | 1121 | 1227 | Hy3 |
| Design Arena: SVG | 949 | 1200 | Hy3 |
| Design Arena: ASCII art | 1062 | 1152 | Hy3 |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index116
| Benchmark | Mistral Medium 3.5 | Hy3 | Leader |
|---|---|---|---|
| SAGE (Vals AI) | 37.6% | 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% | 79.0% | Hy3 |
| 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 | 1438 | Hy3 |
| LMArena Text: instruction following | 1415 | 1426 | Hy3 |
| LMArena Text: creative writing | 1374 | 1403 | Hy3 |
| LMArena Vision | 1222 | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Text: English | 1433 | 1448 | Hy3 |
| LMArena Text: non-English | 1404 | 1426 | Hy3 |
| LMArena Text: Chinese | 1444 | 1485 | Hy3 |
| LMArena Text: German | 1453 | 1449 | Mistral Medium 3.5 |
| LMArena Text: Japanese | Not measured | 1397 | Only Hy3 measured |
| LMArena Text: Korean | 1384 | 1396 | Hy3 |
| LMArena Text: French | 1448 | 1456 | Hy3 |
| LMArena Text: Spanish | 1411 | 1457 | Hy3 |
| LMArena Text: Russian | 1395 | 1432 | Hy3 |
| LMArena Text: Polish | 1430 | 1447 | Hy3 |
| LMArena Text: multi-turn | 1423 | 1436 | Hy3 |
| LMArena Text: longer queries | 1415 | 1442 | Hy3 |
| LMArena Text: writing and language | 1384 | 1414 | Hy3 |
| LMArena Text: entertainment and media | 1382 | 1400 | Hy3 |
| 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 |
| 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 | Mistral Medium 3.5 | 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 Medium 3.5 | Tencent Hy3 |
|---|---|---|
| Maker | Mistral AI | Tencent |
| Weights | No public weights listed | Open weights |
| Released | April 30, 2026 | July 6, 2026 |
| Context window | 262K | 262K |
| Input $/Mtok | $1.50 | $0.132 |
| Output $/Mtok | $7.50 | $0.528 |
| Coding index | 25.5 | Not benchmarked |
| Independent measurements behind it | 3 | 1 |
| Cost per solved task | $6.02 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Mistral Medium 3.5 better than Hy3 for coding?
Only Mistral Medium 3.5 has a coding score, 25.5 on the Vibe Coding Index; Hy3 has none, so the two cannot be ranked on coding. Pick Hy3 for output tokens 14.2x cheaper ($0.528 vs $7.50 per million) and work measured by LMArena WebDev or SciCode, where it leads.
Which is cheaper, Mistral Medium 3.5 or Hy3?
Mistral Medium 3.5 costs $1.50 per million input tokens and $7.50 per million output tokens; Hy3 costs $0.132 and $0.528. Cost per solved task is known for Mistral Medium 3.5 only.
Which has the bigger context window, Mistral Medium 3.5 or Hy3?
Neither: both take 262K tokens.
How many benchmarks is the Mistral Medium 3.5 vs Hy3 comparison based on?
43 benchmarks have a result for both models as of October 22, 2026. Mistral Medium 3.5's coding index rests on 3 independent benchmarks and Hy3's on 1. Where only one model has a result, the page says so instead of naming a winner.