Mistral Medium 3.5 vs Sakana Namazu
Sakana Namazu costs 1.9x less per output token than Mistral Medium 3.5 ($4.00 vs $7.50 per million). Updated October 23, 2026; no benchmark has tested both models yet.
- Coding
- 25.5
- Overall
- 37.3
- Output $/M
- $7.50
- Coding
- No data
- Overall
- No data
- Output $/M
- $4.00
Mistral Medium 3.5 or Sakana Namazu: which to pick
Only Mistral Medium 3.5 has a coding score, 25.5 on the Vibe Coding Index; Sakana Namazu has none, so the two cannot be ranked on coding.
Pick Sakana Namazu for output tokens 1.9x cheaper ($4.00 vs $7.50 per million).
No benchmark has tested both yet. Mistral Medium 3.5 has results on LMArena WebDev, AA Coding Index and SWE-bench Verified (Vals AI); Sakana Namazu has none yet. Compare them on price and context instead.
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
No call
Only Mistral Medium 3.5 has a Design Arena: websites result, 1142.
Directional only
Long documents
Listed context window
No call
Both take 262K tokens.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Sakana Namazu
Mistral Medium 3.5 $0.0053, Sakana Namazu $0.0029 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, Sakana Namazu not benchmarked.
- Widest category
- None yet: no category has been tested on both models.
- Widest single gap
- None yet: no benchmark has tested both models.
- Output price
- Mistral Medium 3.5 $7.50 against Sakana Namazu $4.00 per million output tokens, 1.9x apart.
- Context window
- Both take 262K tokens.
Benchmark by benchmark
Every board either model has a result on, a category to a fold; bars are each result on a 0 to 100 scale. Only one model is measured on each, so no row names a leader.
CodingDirectional onlySix of these boards feed the Vibe Coding Index13 boards measured
| Benchmark | Mistral Medium 3.5 | Sakana Namazu | 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 |
| 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% | 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 | 1461 | 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 | 1309 | Not measured | Only Mistral Medium 3.5 measured |
| Neither model has a result on the other 30 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
| Benchmark | Mistral Medium 3.5 | Sakana Namazu | 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 measured
| Benchmark | Mistral Medium 3.5 | Sakana Namazu | 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 36 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index9 boards measured
| Benchmark | Mistral Medium 3.5 | Sakana Namazu | 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 | 1436 | 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 14 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index3 boards measured
| Benchmark | Mistral Medium 3.5 | Sakana Namazu | 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 measured
| Benchmark | Mistral Medium 3.5 | Sakana Namazu | 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 measured
| Benchmark | Mistral Medium 3.5 | Sakana Namazu | Leader |
|---|---|---|---|
| Design Arena: websites | 1142 | Not measured | Only Mistral Medium 3.5 measured |
| Design Arena: UI components | 1076 | Not measured | Only Mistral Medium 3.5 measured |
| Design Arena: game dev | 1079 | Not measured | Only Mistral Medium 3.5 measured |
| Design Arena: data viz | 1121 | Not measured | Only Mistral Medium 3.5 measured |
| Design Arena: 3D | 1061 | Not measured | Only Mistral Medium 3.5 measured |
| Design Arena: all code categories | 1121 | Not measured | Only Mistral Medium 3.5 measured |
| Design Arena: SVG | 949 | Not measured | Only Mistral Medium 3.5 measured |
| Design Arena: ASCII art | 1062 | 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 index31 boards measured
| Benchmark | Mistral Medium 3.5 | Sakana Namazu | 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% | 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 | 1444 | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Text: German | 1455 | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Text: Korean | 1384 | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Text: French | 1448 | 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 | 993 | Not measured | Only Mistral Medium 3.5 measured |
| Neither model has a result on the other 17 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
Sakana Namazu costs less
Repository review
50K input + 3K output tokens
Sakana Namazu costs less
Agent loop
200K input + 10K output tokens
Sakana Namazu 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 | Sakana Namazu |
|---|---|---|
| Maker | Mistral AI | Sakana |
| Weights | No public weights listed | No public weights listed |
| Released | April 30, 2026 | August 11, 2026 |
| Context window | 262K | 262K |
| Input $/Mtok | $1.50 | $0.95 |
| Output $/Mtok | $7.50 | $4.00 |
| Coding index | 25.5 | Not benchmarked |
| Independent measurements behind it | 3 | 0 |
| Cost per solved task | $6.02 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Mistral Medium 3.5 better than Sakana Namazu for coding?
Only Mistral Medium 3.5 has a coding score, 25.5 on the Vibe Coding Index; Sakana Namazu has none, so the two cannot be ranked on coding. Pick Sakana Namazu for output tokens 1.9x cheaper ($4.00 vs $7.50 per million).
Which is cheaper, Mistral Medium 3.5 or Sakana Namazu?
Mistral Medium 3.5 costs $1.50 per million input tokens and $7.50 per million output tokens; Sakana Namazu costs $0.95 and $4.00. Cost per solved task is known for Mistral Medium 3.5 only.
Which has the bigger context window, Mistral Medium 3.5 or Sakana Namazu?
Neither: both take 262K tokens.
Has any benchmark tested both Mistral Medium 3.5 and Sakana Namazu?
No benchmark has tested both yet. Mistral Medium 3.5 has results on LMArena WebDev, AA Coding Index and SWE-bench Verified (Vals AI); Sakana Namazu has none yet. Compare them on price and context instead. Data as of October 23, 2026.