Muse Glimmer 30B vs Mistral Large 2407
Muse Glimmer 30B leads Mistral Large 2407 on the Artificial Analysis Intelligence Index, 17.5 to 7.6, and Muse Glimmer 30B costs 4.4x less per output token ($1.35 vs $6.00 per million). Updated October 22, 2026; 1 benchmarks have a result for both.
Muse Glimmer 30B or Mistral Large 2407: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick Muse Glimmer 30B for output tokens 4.4x cheaper ($1.35 vs $6.00 per million).
- Shared results
- 1
- Muse Glimmer 30B only
- 4
- Mistral Large 2407 only
- 16
- Like-for-like categories
- 1 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
Neither has a coding score yet.
One side not measured
Intelligence
AA Intelligence Index
Muse Glimmer 30B
Muse Glimmer 30B leads, 17.5 against 7.6.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only Muse Glimmer 30B has a AA Agentic Index result, 8.5.
Directional only
Long documents
Listed context window
No call
Both take 131K tokens.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Muse Glimmer 30B
Muse Glimmer 30B $0.0010, Mistral Large 2407 $0.0050 per turn.
List prices
At a glance
- Coding index
- Muse Glimmer 30B not benchmarked, Mistral Large 2407 not benchmarked.
- Widest category
- Intelligence, 9.9 points apart on average over 1 shared benchmark.
- Widest single gap
- AA Intelligence Index: Muse Glimmer 30B 17.5 against Mistral Large 2407 7.6, 9.9 points apart on a 0 to 100 scale.
- Output price
- Muse Glimmer 30B $1.35 against Mistral Large 2407 $6.00 per million output tokens, 4.4x apart.
- Context window
- Both take 131K 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 | Muse Glimmer 30B | Bars | Mistral Large 2407 | Ties |
|---|---|---|---|---|
| Intelligence | 1 | 0 | ||
| All shared boards | 1 | 0 |
CodingDirectional onlySix of these boards feed the Vibe Coding Index3 boards, none shared
| Benchmark | Muse Glimmer 30B | Mistral Large 2407 | Leader |
|---|---|---|---|
| AA Coding Index | 49.0 | Not measured | Only Muse Glimmer 30B measured |
| LiveCodeBench (Artificial Analysis run) | Not measured | 26.7% | Only Mistral Large 2407 measured |
| ALE-Bench | 962.5 | Not measured | Only Muse Glimmer 30B measured |
| Neither model has a result on the other 36 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Muse Glimmer 30B | Mistral Large 2407 | Leader |
|---|---|---|---|
| AA Intelligence Index | 17.5 | 7.6 | Muse Glimmer 30B |
| Neither model has a result on the other 1 board here | |||
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | Muse Glimmer 30B | Mistral Large 2407 | Leader |
|---|---|---|---|
| AA Agentic Index | 8.5 | Not measured | Only Muse Glimmer 30B measured |
| τ²-Bench Telecom | Not measured | 33.0% | Only Mistral Large 2407 measured |
| Neither model has a result on the other 39 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
| Benchmark | Muse Glimmer 30B | Mistral Large 2407 | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | Not measured | 47.2% | Only Mistral Large 2407 measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 2.9% | Only Mistral Large 2407 measured |
| GPQA Diamond (Epoch AI run) | Not measured | 49.0% | Only Mistral Large 2407 measured |
| SimpleBench | Not measured | 22.5% | Only Mistral Large 2407 measured |
| Neither model has a result on the other 18 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
| Benchmark | Muse Glimmer 30B | Mistral Large 2407 | Leader |
|---|---|---|---|
| AA Math Index | Not measured | 0.0 | Only Mistral Large 2407 measured |
| AIME 2025 (Artificial Analysis run) | Not measured | 0.0% | Only Mistral Large 2407 measured |
| OTIS Mock AIME | Not measured | 8.5% | Only Mistral Large 2407 measured |
| MATH level 5 | Not measured | 44.8% | Only Mistral Large 2407 measured |
| Neither model has a result on the other 9 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | Muse Glimmer 30B | Mistral Large 2407 | Leader |
|---|---|---|---|
| MMLU Pro (Artificial Analysis run) | Not measured | 68.3% | Only Mistral Large 2407 measured |
| MMLU | Not measured | 80.0% | Only Mistral Large 2407 measured |
| Neither model has a result on the other 16 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | Muse Glimmer 30B | Mistral Large 2407 | Leader |
|---|---|---|---|
| Design Arena: game dev | 1144 | Not measured | Only Muse Glimmer 30B measured |
| Neither model has a result on the other 8 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
| Benchmark | Muse Glimmer 30B | Mistral Large 2407 | Leader |
|---|---|---|---|
| IFBench | Not measured | 31.6% | Only Mistral Large 2407 measured |
| Long context reasoning (AA-LCR) | Not measured | 2.0% | Only Mistral Large 2407 measured |
| DTBench | Not measured | 61.2% | Only Mistral Large 2407 measured |
| Creative writing (Lech Mazur) | Not measured | 69.0% | Only Mistral Large 2407 measured |
| Neither model has a result on the other 42 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Muse Glimmer 30B | Mistral Large 2407 | 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 Glimmer 30B costs less
Repository review
50K input + 3K output tokens
Muse Glimmer 30B costs less
Agent loop
200K input + 10K output tokens
Muse Glimmer 30B 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 Glimmer 30B | Mistral Large 2407 |
|---|---|---|
| Maker | Meta | Mistral AI |
| Weights | Open weights | No public weights listed |
| Released | August 9, 2026 | November 19, 2024 |
| Context window | 131K | 131K |
| Input $/Mtok | $0.325 | $2.00 |
| Output $/Mtok | $1.35 | $6.00 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 0 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Muse Glimmer 30B better than Mistral Large 2407 for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Muse Glimmer 30B for output tokens 4.4x cheaper ($1.35 vs $6.00 per million).
Which is cheaper, Muse Glimmer 30B or Mistral Large 2407?
Muse Glimmer 30B costs $0.325 per million input tokens and $1.35 per million output tokens; Mistral Large 2407 costs $2.00 and $6.00. Cost per solved task is known for neither of them.
Which has the bigger context window, Muse Glimmer 30B or Mistral Large 2407?
Neither: both take 131K tokens.
How many benchmarks is the Muse Glimmer 30B vs Mistral Large 2407 comparison based on?
1 benchmarks have a result for both models as of October 22, 2026. Muse Glimmer 30B's coding index rests on 0 independent benchmarks and Mistral Large 2407's on 0. Where only one model has a result, the page says so instead of naming a winner.