Muse Glimmer 30B vs Qwen3.5-9B
Muse Glimmer 30B leads Qwen3.5-9B on the Artificial Analysis Intelligence Index, 17.5 to 13.3, and Qwen3.5-9B costs 9.0x less per output token ($0.15 vs $1.35 per million). Updated October 22, 2026; 2 benchmarks have a result for both.
Muse Glimmer 30B or Qwen3.5-9B: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Compare them on price, context and the boards below.
- Shared results
- 2
- Muse Glimmer 30B only
- 3
- Qwen3.5-9B only
- 13
- Like-for-like categories
- 2 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 13.3.
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
Qwen3.5-9B
Qwen3.5-9B takes 262K tokens against 131K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen3.5-9B
Muse Glimmer 30B $0.0010, Qwen3.5-9B $0.0002 per turn.
List prices
At a glance
- Coding index
- Muse Glimmer 30B not benchmarked, Qwen3.5-9B not benchmarked.
- Widest category
- Coding, 25.5 points apart on average over 1 shared benchmark.
- Widest single gap
- AA Coding Index: Muse Glimmer 30B 49.0 against Qwen3.5-9B 23.5, 25.5 points apart on a 0 to 100 scale.
- Output price
- Muse Glimmer 30B $1.35 against Qwen3.5-9B $0.15 per million output tokens, 9.0x apart.
- Context window
- Muse Glimmer 30B takes 131K tokens, Qwen3.5-9B 262K.
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 | Qwen3.5-9B | Ties |
|---|---|---|---|---|
| Coding | 1 | 0 | ||
| Intelligence | 1 | 0 | ||
| All shared boards | 2 | 0 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index10
| Benchmark | Muse Glimmer 30B | Qwen3.5-9B | Leader |
|---|---|---|---|
| AA Coding Index | 49.0 | 23.5 | Muse Glimmer 30B |
| SciCode | Not measured | 29.5% | Only Qwen3.5-9B measured |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 24.2% | Only Qwen3.5-9B measured |
| Terminal-Bench | Not measured | 9.2% | Only Qwen3.5-9B measured |
| ALE-Bench | 962.5 | Not measured | Only Muse Glimmer 30B measured |
| Neither model has a result on the other 34 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Muse Glimmer 30B | Qwen3.5-9B | Leader |
|---|---|---|---|
| AA Intelligence Index | 17.5 | 13.3 | Muse Glimmer 30B |
| Epoch Capabilities Index | Not measured | 139.3 | Only Qwen3.5-9B measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | Muse Glimmer 30B | Qwen3.5-9B | Leader |
|---|---|---|---|
| AA Agentic Index | 8.5 | Not measured | Only Muse Glimmer 30B measured |
| τ²-Bench Telecom | Not measured | 86.8% | Only Qwen3.5-9B measured |
| Neither model has a result on the other 39 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
| Benchmark | Muse Glimmer 30B | Qwen3.5-9B | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | Not measured | 80.6% | Only Qwen3.5-9B measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 14.9% | Only Qwen3.5-9B measured |
| GPQA Diamond (Epoch AI run) | Not measured | 79.0% | Only Qwen3.5-9B measured |
| Neither model has a result on the other 19 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | Muse Glimmer 30B | Qwen3.5-9B | Leader |
|---|---|---|---|
| OTIS Mock AIME | Not measured | 61.7% | Only Qwen3.5-9B measured |
| Neither model has a result on the other 12 boards here | |||
KnowledgeNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Muse Glimmer 30B | Qwen3.5-9B | Leader |
|---|---|---|---|
| Neither model has a result on 18 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | Muse Glimmer 30B | Qwen3.5-9B | 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 | Qwen3.5-9B | Leader |
|---|---|---|---|
| IFBench | Not measured | 66.7% | Only Qwen3.5-9B measured |
| Long context reasoning (AA-LCR) | Not measured | 70.0% | Only Qwen3.5-9B measured |
| DTBench | Not measured | 71.2% | Only Qwen3.5-9B measured |
| LMCA | Not measured | 24.5% | Only Qwen3.5-9B 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 | Qwen3.5-9B | 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
Qwen3.5-9B costs less
Repository review
50K input + 3K output tokens
Qwen3.5-9B costs less
Agent loop
200K input + 10K output tokens
Qwen3.5-9B 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 | Qwen3.5-9B |
|---|---|---|
| Maker | Meta | Qwen |
| Weights | Open weights | Open weights |
| Released | August 9, 2026 | March 10, 2026 |
| Context window | 131K | 262K |
| Input $/Mtok | $0.325 | $0.10 |
| Output $/Mtok | $1.35 | $0.15 |
| 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 Qwen3.5-9B for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Compare them on price, context and the boards below.
Which is cheaper, Muse Glimmer 30B or Qwen3.5-9B?
Muse Glimmer 30B costs $0.325 per million input tokens and $1.35 per million output tokens; Qwen3.5-9B costs $0.10 and $0.15. Cost per solved task is known for neither of them.
Which has the bigger context window, Muse Glimmer 30B or Qwen3.5-9B?
Qwen3.5-9B, with 262K tokens against 131K.
How many benchmarks is the Muse Glimmer 30B vs Qwen3.5-9B comparison based on?
2 benchmarks have a result for both models as of October 22, 2026. Muse Glimmer 30B's coding index rests on 0 independent benchmarks and Qwen3.5-9B's on 0. Where only one model has a result, the page says so instead of naming a winner.