Schematron V2 Small vs Mistral Large 4
Schematron V2 Small costs 18.2x less per output token than Mistral Large 4 ($0.23 vs $4.18 per million). Updated October 21, 2026; no benchmark has tested both models yet.
- Coding
- No data
- Overall
- No data
- Output $/M
- $0.23
- Coding
- 56.4
- Overall
- 54.6
- Output $/M
- $4.18
Schematron V2 Small or Mistral Large 4: which to pick
Only Mistral Large 4 has a coding score, 56.4 on the Vibe Coding Index; Schematron V2 Small has none, so the two cannot be ranked on coding.
Pick Schematron V2 Small for output tokens 18.2x cheaper ($0.23 vs $4.18 per million).
No benchmark has tested both yet. Schematron V2 Small has none yet; Mistral Large 4 on LiveBench coding, LMArena WebDev and Terminal-Bench 4 (Vals AI). 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 Large 4 has a coding score, so no call is made.
One side not measured
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
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 128K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Schematron V2 Small
Schematron V2 Small $0.0002, Mistral Large 4 $0.0034 per turn.
List prices
At a glance
- Coding index
- Schematron V2 Small not benchmarked, Mistral Large 4 56.4 from 5 benchmarks.
- 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
- Schematron V2 Small $0.23 against Mistral Large 4 $4.18 per million output tokens, 18.2x apart.
- Context window
- Schematron V2 Small takes 128K tokens, Mistral Large 4 1.05M.
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 Index15 boards measured
| Benchmark | Schematron V2 Small | Mistral Large 4 | Leader |
|---|---|---|---|
| LiveBench coding | Not measured | 60.0% | Only Mistral Large 4 measured |
| LMArena WebDev | Not measured | 1543 | Only Mistral Large 4 measured |
| Terminal-Bench 4 (Vals AI) | Not measured | 27.8% | Only Mistral Large 4 measured |
| Vibe Code Bench (Vals AI) | Not measured | 78.4% | Only Mistral Large 4 measured |
| Code migration (Vals AI) | Not measured | 30.6% | Only Mistral Large 4 measured |
| IOI (Vals AI) | Not measured | 45.3% | Only Mistral Large 4 measured |
| SWE-bench Multimodal (Vals AI) | Not measured | 33.1% | Only Mistral Large 4 measured |
| Vibe Code Bench 1-100 (Vals AI) | Not measured | 14.3% | Only Mistral Large 4 measured |
| SciCode | Not measured | 54.2% | Only Mistral Large 4 measured |
| FrontierCode | Not measured | 39.4% | Only Mistral Large 4 measured |
| ALE-Bench | Not measured | 1213.2 | Only Mistral Large 4 measured |
| LMArena Text: coding | Not measured | 1478 | Only Mistral Large 4 measured |
| LMArena Text: software and IT | Not measured | 1467 | Only Mistral Large 4 measured |
| LMArena WebDev: React | Not measured | 1559 | Only Mistral Large 4 measured |
| LMArena WebDev: HTML | Not measured | 1487 | Only Mistral Large 4 measured |
| Neither model has a result on the other 24 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
| Benchmark | Schematron V2 Small | Mistral Large 4 | Leader |
|---|---|---|---|
| AA Intelligence Index | Not measured | 38.4 | Only Mistral Large 4 measured |
| Epoch Capabilities Index | Not measured | 150.0 | Only Mistral Large 4 measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index9 boards measured
| Benchmark | Schematron V2 Small | Mistral Large 4 | Leader |
|---|---|---|---|
| LiveBench research | Not measured | 28.1% | Only Mistral Large 4 measured |
| LiveBench browser | Not measured | 8.0% | Only Mistral Large 4 measured |
| LiveBench long agentic | Not measured | 11.8% | Only Mistral Large 4 measured |
| Finance Agent (Vals AI) | Not measured | 54.7% | Only Mistral Large 4 measured |
| Tax Agent Bench (Vals AI) | Not measured | 30.4% | Only Mistral Large 4 measured |
| Legal Research Bench (Vals AI) | Not measured | 31.7% | Only Mistral Large 4 measured |
| Harvey's Legal Agent Benchmark (Vals AI) | Not measured | 17.5% | Only Mistral Large 4 measured |
| Excel Modeling Benchmark (Vals AI) | Not measured | 56.2% | Only Mistral Large 4 measured |
| BioMysteryBench (Vals AI) | Not measured | 67.0% | Only Mistral Large 4 measured |
| Neither model has a result on the other 32 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index10 boards measured
| Benchmark | Schematron V2 Small | Mistral Large 4 | Leader |
|---|---|---|---|
| LiveBench reasoning | Not measured | 83.9% | Only Mistral Large 4 measured |
| MysteryMechanism (Vals AI) | Not measured | 12.2% | Only Mistral Large 4 measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 35.0% | Only Mistral Large 4 measured |
| GPQA Diamond (Epoch AI run) | Not measured | 88.1% | Only Mistral Large 4 measured |
| Chess puzzles | Not measured | 33.0% | Only Mistral Large 4 measured |
| Mystery game puzzles | Not measured | 17.0% | Only Mistral Large 4 measured |
| LMArena Text: hard prompts | Not measured | 1444 | Only Mistral Large 4 measured |
| LMArena Text: expert | Not measured | 1444 | Only Mistral Large 4 measured |
| LMArena Text: hard prompts in English | Not measured | 1442 | Only Mistral Large 4 measured |
| LMArena Vision: diagrams | Not measured | 1288 | Only Mistral Large 4 measured |
| Neither model has a result on the other 12 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index6 boards measured
| Benchmark | Schematron V2 Small | Mistral Large 4 | Leader |
|---|---|---|---|
| OTIS Mock AIME | Not measured | 98.3% | Only Mistral Large 4 measured |
| FrontierMath, tiers 1 to 3 | Not measured | 58.6% | Only Mistral Large 4 measured |
| FrontierMath, tier 4 | Not measured | 26.8% | Only Mistral Large 4 measured |
| ProofBench | Not measured | 10.0% | Only Mistral Large 4 measured |
| LMArena Text: math | Not measured | 1469 | Only Mistral Large 4 measured |
| LMArena Text: mathematical work | Not measured | 1462 | Only Mistral Large 4 measured |
| Neither model has a result on the other 7 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index6 boards measured
| Benchmark | Schematron V2 Small | Mistral Large 4 | Leader |
|---|---|---|---|
| MedCode (Vals AI) | Not measured | 40.7% | Only Mistral Large 4 measured |
| SimpleQA Verified | Not measured | 20.0% | Only Mistral Large 4 measured |
| LMArena Text: science | Not measured | 1448 | Only Mistral Large 4 measured |
| LMArena Text: medicine and healthcare | Not measured | 1433 | Only Mistral Large 4 measured |
| LMArena Text: legal and government | Not measured | 1425 | Only Mistral Large 4 measured |
| LMArena Text: business and finance | Not measured | 1439 | Only Mistral Large 4 measured |
| Neither model has a result on the other 12 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index9 boards measured
| Benchmark | Schematron V2 Small | Mistral Large 4 | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1258 | Only Mistral Large 4 measured |
| Design Arena: UI components | Not measured | 1275 | Only Mistral Large 4 measured |
| Design Arena: game dev | Not measured | 1226 | Only Mistral Large 4 measured |
| Design Arena: data viz | Not measured | 1274 | Only Mistral Large 4 measured |
| Design Arena: 3D | Not measured | 1253 | Only Mistral Large 4 measured |
| Design Arena: all code categories | Not measured | 1259 | Only Mistral Large 4 measured |
| Design Arena: SVG | Not measured | 1233 | Only Mistral Large 4 measured |
| Design Arena: ASCII art | Not measured | 1202 | Only Mistral Large 4 measured |
| LiveBench design | Not measured | 65.6% | Only Mistral Large 4 measured |
GeneralDirectional onlyPublic boards, shown as published, kept out of the index24 boards measured
| Benchmark | Schematron V2 Small | Mistral Large 4 | Leader |
|---|---|---|---|
| LiveBench data analysis | Not measured | 76.5% | Only Mistral Large 4 measured |
| MedScribe (Vals AI) | Not measured | 80.4% | Only Mistral Large 4 measured |
| Long context reasoning (AA-LCR) | Not measured | 81.3% | Only Mistral Large 4 measured |
| DTBench | Not measured | 88.2% | Only Mistral Large 4 measured |
| LMCA | Not measured | 35.8% | Only Mistral Large 4 measured |
| Surface Evolver Bench | Not measured | 28.1% | Only Mistral Large 4 measured |
| Furniture assembly | Not measured | 20.8% | Only Mistral Large 4 measured |
| LMArena Text | Not measured | 1431 | Only Mistral Large 4 measured |
| LMArena Text: instruction following | Not measured | 1422 | Only Mistral Large 4 measured |
| LMArena Text: creative writing | Not measured | 1363 | Only Mistral Large 4 measured |
| LMArena Vision | Not measured | 1272 | Only Mistral Large 4 measured |
| LMArena Text: English | Not measured | 1433 | Only Mistral Large 4 measured |
| LMArena Text: non-English | Not measured | 1422 | Only Mistral Large 4 measured |
| LMArena Text: Chinese | Not measured | 1492 | Only Mistral Large 4 measured |
| LMArena Text: Japanese | Not measured | 1415 | Only Mistral Large 4 measured |
| LMArena Text: French | Not measured | 1492 | Only Mistral Large 4 measured |
| LMArena Text: Spanish | Not measured | 1455 | Only Mistral Large 4 measured |
| LMArena Text: Russian | Not measured | 1417 | Only Mistral Large 4 measured |
| LMArena Text: multi-turn | Not measured | 1435 | Only Mistral Large 4 measured |
| LMArena Text: longer queries | Not measured | 1428 | Only Mistral Large 4 measured |
| LMArena Text: writing and language | Not measured | 1386 | Only Mistral Large 4 measured |
| LMArena Text: entertainment and media | Not measured | 1378 | Only Mistral Large 4 measured |
| LMArena Vision: English | Not measured | 1283 | Only Mistral Large 4 measured |
| LMArena Vision: reading text | Not measured | 1284 | Only Mistral Large 4 measured |
| Neither model has a result on the other 22 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
Schematron V2 Small costs less
Repository review
50K input + 3K output tokens
Schematron V2 Small costs less
Agent loop
200K input + 10K output tokens
Schematron V2 Small 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 | Inference.net Schematron V2 Small | Mistral Large 4 |
|---|---|---|
| Maker | Inference.net | Mistral AI |
| Weights | Open weights | No public weights listed |
| Released | September 12, 2026 | October 6, 2026 |
| Context window | 128K | 1.05M |
| Input $/Mtok | $0.05 | $1.36 |
| Output $/Mtok | $0.23 | $4.18 |
| Coding index | Not benchmarked | 56.4 |
| Independent measurements behind it | 0 | 5 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Schematron V2 Small better than Mistral Large 4 for coding?
Only Mistral Large 4 has a coding score, 56.4 on the Vibe Coding Index; Schematron V2 Small has none, so the two cannot be ranked on coding. Pick Schematron V2 Small for output tokens 18.2x cheaper ($0.23 vs $4.18 per million).
Which is cheaper, Schematron V2 Small or Mistral Large 4?
Schematron V2 Small costs $0.05 per million input tokens and $0.23 per million output tokens; Mistral Large 4 costs $1.36 and $4.18. Cost per solved task is known for neither of them.
Which has the bigger context window, Schematron V2 Small or Mistral Large 4?
Mistral Large 4, with 1.05M tokens against 128K.
Has any benchmark tested both Schematron V2 Small and Mistral Large 4?
No benchmark has tested both yet. Schematron V2 Small has none yet; Mistral Large 4 on LiveBench coding, LMArena WebDev and Terminal-Bench 4 (Vals AI). Compare them on price and context instead. Data as of October 21, 2026.