Muse Spark 1.3 vs Mistral Large
Muse Spark 1.3 leads Mistral Large on the Artificial Analysis Intelligence Index, 48.1 to 5.8, and Muse Spark 1.3 costs 1.4x less per output token ($4.25 vs $6.00 per million). Updated October 21, 2026; 33 benchmarks have a result for both.
Muse Spark 1.3 or Mistral Large: which to pick
Only Muse Spark 1.3 has a coding score, 57.4 on the Vibe Coding Index; Mistral Large has none, so the two cannot be ranked on coding.
Compare them on price, context and the boards below.
- Shared results
- 33
- Muse Spark 1.3 only
- 59
- Mistral Large only
- 11
- 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 Muse Spark 1.3 has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
Muse Spark 1.3
Muse Spark 1.3 leads, 48.1 against 5.8.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only Muse Spark 1.3 has a AA Agentic Index result, 55.5.
Directional only
Reasoning
GPQA Diamond
No call
Only Mistral Large has a GPQA Diamond result, 47.7%.
Directional only
Math
AIME
No call
Only Mistral Large has a AIME result, 9.2%.
Directional only
Knowledge
MMLU Pro
No call
Only Mistral Large has a MMLU Pro result, 69.7%.
Directional only
Web design
Design Arena: websites
No call
Only Muse Spark 1.3 has a Design Arena: websites result, 1356.
Directional only
Long documents
Listed context window
Muse Spark 1.3
Muse Spark 1.3 takes 1.05M tokens against 128K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Muse Spark 1.3
Muse Spark 1.3 $0.0034, Mistral Large $0.0050 per turn.
List prices
At a glance
- Coding index
- Muse Spark 1.3 57.4 from 4 benchmarks, Mistral Large not benchmarked.
- Widest category
- Reasoning, 47.2 points apart on average over 5 shared benchmarks.
- Widest single gap
- GPQA Diamond (Artificial Analysis run): Muse Spark 1.3 94.1% against Mistral Large 35.1%, 59.0 points apart on a 0 to 100 scale.
- Output price
- Muse Spark 1.3 $4.25 against Mistral Large $6.00 per million output tokens, 1.4x apart.
- Context window
- Muse Spark 1.3 takes 1.05M tokens, Mistral Large 128K.
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 | Muse Spark 1.3 | Bars | Mistral Large | Ties |
|---|---|---|---|---|
| Coding | 2 | 0 | ||
| Intelligence | 2 | 0 | ||
| Reasoning | 5 | 0 | ||
| Math | 2 | 0 | ||
| Knowledge | 4 | 0 | ||
| General | 18 | 0 | ||
| All shared boards | 33 | 0 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index20
| Benchmark | Muse Spark 1.3 | Mistral Large | Leader |
|---|---|---|---|
| LiveBench coding | 90.2% | Not measured | Only Muse Spark 1.3 measured |
| LMArena WebDev | 1659 | Not measured | Only Muse Spark 1.3 measured |
| AA Coding Index | 75.8 | Not measured | Only Muse Spark 1.3 measured |
| LiveCodeBench (Vals AI) | Not measured | 37.1% | Only Mistral Large measured |
| Terminal-Bench 4 (Vals AI) | 10.6% | Not measured | Only Muse Spark 1.3 measured |
| Vibe Code Bench (Vals AI) | 82.9% | Not measured | Only Muse Spark 1.3 measured |
| Code migration (Vals AI) | 27.6% | Not measured | Only Muse Spark 1.3 measured |
| ProgramBench (Vals AI) | 0.5% | Not measured | Only Muse Spark 1.3 measured |
| IOI (Vals AI) | 43.9% | Not measured | Only Muse Spark 1.3 measured |
| Terminal-Bench 2.1 (Vals AI) | 72.3% | Not measured | Only Muse Spark 1.3 measured |
| CyberBench (Vals AI) | 69.4% | Not measured | Only Muse Spark 1.3 measured |
| LiveCodeBench (Artificial Analysis run) | Not measured | 17.8% | Only Mistral Large measured |
| SciCode | 59.7% | Not measured | Only Muse Spark 1.3 measured |
| FrontierSWE | 25.8% | Not measured | Only Muse Spark 1.3 measured |
| ALE-Bench | 1688.3 | Not measured | Only Muse Spark 1.3 measured |
| LMArena Text: coding | 1510 | 1275 | Muse Spark 1.3 |
| LMArena Text: software and IT | 1511 | 1274 | Muse Spark 1.3 |
| LMArena WebDev: React | 1672 | Not measured | Only Muse Spark 1.3 measured |
| LMArena WebDev: HTML | 1653 | Not measured | Only Muse Spark 1.3 measured |
| LMArena WebDev: from an image | 1640 | Not measured | Only Muse Spark 1.3 measured |
| Neither model has a result on the other 19 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Muse Spark 1.3 | Mistral Large | Leader |
|---|---|---|---|
| AA Intelligence Index | 48.1 | 5.8 | Muse Spark 1.3 |
| Epoch Capabilities Index | 157.2 | 122.1 | Muse Spark 1.3 |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index16 boards, none shared
| Benchmark | Muse Spark 1.3 | Mistral Large | Leader |
|---|---|---|---|
| AA Agentic Index | 55.5 | Not measured | Only Muse Spark 1.3 measured |
| Design Arena: agents building web apps | 1297 | Not measured | Only Muse Spark 1.3 measured |
| Design Arena: agents building full-stack apps | 1295 | Not measured | Only Muse Spark 1.3 measured |
| Design Arena: agents building mobile apps | 1217 | Not measured | Only Muse Spark 1.3 measured |
| Design Arena: agents building Godot games | 1241 | Not measured | Only Muse Spark 1.3 measured |
| Design Arena: PowerPoint slides | 1243 | Not measured | Only Muse Spark 1.3 measured |
| Design Arena: spreadsheets | 1043 | Not measured | Only Muse Spark 1.3 measured |
| LiveBench research | 68.6% | Not measured | Only Muse Spark 1.3 measured |
| LiveBench browser | 80.0% | Not measured | Only Muse Spark 1.3 measured |
| LiveBench long agentic | 40.4% | Not measured | Only Muse Spark 1.3 measured |
| Finance Agent (Vals AI) | 58.9% | Not measured | Only Muse Spark 1.3 measured |
| Tax Agent Bench (Vals AI) | 36.0% | Not measured | Only Muse Spark 1.3 measured |
| Legal Research Bench (Vals AI) | 40.9% | Not measured | Only Muse Spark 1.3 measured |
| Excel Modeling Benchmark (Vals AI) | 62.7% | Not measured | Only Muse Spark 1.3 measured |
| Terminal-Bench-Science (Vals AI) | 4.3% | Not measured | Only Muse Spark 1.3 measured |
| APEX-Agents | 58.6% | Not measured | Only Muse Spark 1.3 measured |
| Neither model has a result on the other 25 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index50
| Benchmark | Muse Spark 1.3 | Mistral Large | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 47.7% | Only Mistral Large measured |
| LiveBench reasoning | 89.7% | Not measured | Only Muse Spark 1.3 measured |
| GPQA Diamond (Artificial Analysis run) | 94.1% | 35.1% | Muse Spark 1.3 |
| Humanity's Last Exam (Artificial Analysis run) | 48.7% | 3.5% | Muse Spark 1.3 |
| Chess puzzles | 37.0% | Not measured | Only Muse Spark 1.3 measured |
| Mystery game puzzles | 25.0% | Not measured | Only Muse Spark 1.3 measured |
| LMArena Text: hard prompts | 1503 | 1257 | Muse Spark 1.3 |
| LMArena Text: expert | 1519 | 1208 | Muse Spark 1.3 |
| LMArena Text: hard prompts in English | 1500 | 1268 | Muse Spark 1.3 |
| LMArena Vision: diagrams | 1330 | Not measured | Only Muse Spark 1.3 measured |
| LMArena Vision: homework | 1296 | Not measured | Only Muse Spark 1.3 measured |
| Neither model has a result on the other 11 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Muse Spark 1.3 | Mistral Large | Leader |
|---|---|---|---|
| AIME | Not measured | 9.2% | Only Mistral Large measured |
| MATH 500 (Vals AI) | Not measured | 74.4% | Only Mistral Large measured |
| MGSM (Vals AI) | Not measured | 87.2% | Only Mistral Large measured |
| OTIS Mock AIME | 99.2% | Not measured | Only Muse Spark 1.3 measured |
| FrontierMath, tiers 1 to 3 | 74.4% | Not measured | Only Muse Spark 1.3 measured |
| FrontierMath, tier 4 | 46.3% | Not measured | Only Muse Spark 1.3 measured |
| ProofBench | 58.0% | Not measured | Only Muse Spark 1.3 measured |
| LMArena Text: math | 1497 | 1261 | Muse Spark 1.3 |
| LMArena Text: mathematical work | 1491 | 1257 | Muse Spark 1.3 |
| Neither model has a result on the other 4 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index40
| Benchmark | Muse Spark 1.3 | Mistral Large | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 69.7% | Only Mistral Large measured |
| TaxEval (Vals AI) | Not measured | 63.8% | Only Mistral Large measured |
| MedQA (Vals AI) | Not measured | 76.2% | Only Mistral Large measured |
| MMLU Pro (Artificial Analysis run) | Not measured | 51.5% | Only Mistral Large measured |
| MMLU | Not measured | 68.8% | Only Mistral Large measured |
| LMArena Text: science | 1507 | 1260 | Muse Spark 1.3 |
| LMArena Text: medicine and healthcare | 1493 | 1255 | Muse Spark 1.3 |
| LMArena Text: legal and government | 1499 | 1275 | Muse Spark 1.3 |
| LMArena Text: business and finance | 1490 | 1238 | Muse Spark 1.3 |
| Neither model has a result on the other 9 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index9 boards, none shared
| Benchmark | Muse Spark 1.3 | Mistral Large | Leader |
|---|---|---|---|
| Design Arena: websites | 1356 | Not measured | Only Muse Spark 1.3 measured |
| Design Arena: UI components | 1351 | Not measured | Only Muse Spark 1.3 measured |
| Design Arena: game dev | 1329 | Not measured | Only Muse Spark 1.3 measured |
| Design Arena: data viz | 1343 | Not measured | Only Muse Spark 1.3 measured |
| Design Arena: 3D | 1359 | Not measured | Only Muse Spark 1.3 measured |
| Design Arena: all code categories | 1353 | Not measured | Only Muse Spark 1.3 measured |
| Design Arena: SVG | 1301 | Not measured | Only Muse Spark 1.3 measured |
| Design Arena: ASCII art | 1280 | Not measured | Only Muse Spark 1.3 measured |
| LiveBench design | 74.8% | Not measured | Only Muse Spark 1.3 measured |
GeneralLike-for-likePublic boards, shown as published, kept out of the index180
| Benchmark | Muse Spark 1.3 | Mistral Large | Leader |
|---|---|---|---|
| LiveBench data analysis | 79.6% | Not measured | Only Muse Spark 1.3 measured |
| Long context reasoning (AA-LCR) | 83.0% | Not measured | Only Muse Spark 1.3 measured |
| DTBench | 96.5% | 60.8% | Muse Spark 1.3 |
| LMCA | 53.9% | Not measured | Only Muse Spark 1.3 measured |
| LMArena Text | 1490 | 1265 | Muse Spark 1.3 |
| LMArena Text: instruction following | 1479 | 1249 | Muse Spark 1.3 |
| LMArena Text: creative writing | 1462 | 1242 | Muse Spark 1.3 |
| LMArena Vision | 1308 | Not measured | Only Muse Spark 1.3 measured |
| LMArena Text: English | 1495 | 1284 | Muse Spark 1.3 |
| LMArena Text: non-English | 1481 | 1235 | Muse Spark 1.3 |
| LMArena Text: Chinese | 1532 | 1239 | Muse Spark 1.3 |
| LMArena Text: German | 1513 | 1242 | Muse Spark 1.3 |
| LMArena Text: Japanese | 1470 | 1170 | Muse Spark 1.3 |
| LMArena Text: Korean | 1490 | 1202 | Muse Spark 1.3 |
| LMArena Text: French | 1511 | 1325 | Muse Spark 1.3 |
| LMArena Text: Spanish | 1496 | 1268 | Muse Spark 1.3 |
| LMArena Text: Russian | 1491 | 1252 | Muse Spark 1.3 |
| LMArena Text: Polish | 1490 | 1157 | Muse Spark 1.3 |
| LMArena Text: multi-turn | 1487 | 1260 | Muse Spark 1.3 |
| LMArena Text: longer queries | 1488 | 1261 | Muse Spark 1.3 |
| LMArena Text: writing and language | 1470 | 1261 | Muse Spark 1.3 |
| LMArena Text: entertainment and media | 1457 | 1230 | Muse Spark 1.3 |
| LMArena Vision: English | 1298 | Not measured | Only Muse Spark 1.3 measured |
| LMArena Vision: Chinese | 1384 | Not measured | Only Muse Spark 1.3 measured |
| LMArena Vision: reading text | 1319 | Not measured | Only Muse Spark 1.3 measured |
| LMArena Vision: humor | 1293 | Not measured | Only Muse Spark 1.3 measured |
| LMArena Vision: creative writing | 1296 | Not measured | Only Muse Spark 1.3 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 | Muse Spark 1.3 | Mistral Large | 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
Muse Spark 1.3 costs less
Repository review
50K input + 3K output tokens
Muse Spark 1.3 costs less
Agent loop
200K input + 10K output tokens
Muse Spark 1.3 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 | Meta Muse Spark 1.3 | Mistral Large |
|---|---|---|
| Maker | Meta | Mistral AI |
| Weights | No public weights listed | No public weights listed |
| Released | September 2, 2026 | February 26, 2024 |
| Context window | 1.05M | 128K |
| Input $/Mtok | $1.25 | $2.00 |
| Output $/Mtok | $4.25 | $6.00 |
| Coding index | 57.4 | Not benchmarked |
| Independent measurements behind it | 4 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Muse Spark 1.3 better than Mistral Large for coding?
Only Muse Spark 1.3 has a coding score, 57.4 on the Vibe Coding Index; Mistral Large has none, so the two cannot be ranked on coding. Compare them on price, context and the boards below.
Which is cheaper, Muse Spark 1.3 or Mistral Large?
Muse Spark 1.3 costs $1.25 per million input tokens and $4.25 per million output tokens; Mistral Large costs $2.00 and $6.00. Cost per solved task is known for neither of them.
Which has the bigger context window, Muse Spark 1.3 or Mistral Large?
Muse Spark 1.3, with 1.05M tokens against 128K.
How many benchmarks is the Muse Spark 1.3 vs Mistral Large comparison based on?
33 benchmarks have a result for both models as of October 21, 2026. Muse Spark 1.3's coding index rests on 4 independent benchmarks and Mistral Large's on 0. Where only one model has a result, the page says so instead of naming a winner.