Gemma 4 31B vs Muse Ember
Muse Ember leads Gemma 4 31B on coding, 64.9 to 21.9 on the Vibe Coding Index, and Gemma 4 31B costs 1.3x less per output token ($0.40 vs $0.50 per million). Updated November 14, 2026; 8 benchmarks have a result for both.
Gemma 4 31B or Muse Ember: which to pick
Pick Muse Ember for coding: it scores 64.9 on the Vibe Coding Index against 21.9 for Gemma 4 31B.
Pick Gemma 4 31B for output tokens 1.3x cheaper ($0.40 vs $0.50 per million).
- Shared results
- 8
- Gemma 4 31B only
- 71
- Muse Ember only
- 7
- Like-for-like categories
- 3 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
Muse Ember
Muse Ember scores 64.9 against 21.9.
2 and 3 benchmarks behind the scores
Intelligence
AA Intelligence Index
No call
Only Gemma 4 31B has a AA Intelligence Index result, 4.4.
Directional only
Agentic work
AA Agentic Index
No call
Only Gemma 4 31B has a AA Agentic Index result, 4.2.
Directional only
General
Vals Index
No call
Only Muse Ember has a Vals Index result, 60.5%.
Directional only
Long documents
Listed context window
Muse Ember
Muse Ember takes 1.05M tokens against 262K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Gemma 4 31B
Gemma 4 31B $0.0003, Muse Ember $0.0003 per turn.
List prices
At a glance
- Coding index
- Gemma 4 31B 21.9 from 2 benchmarks, Muse Ember 64.9 from 3 benchmarks.
- Widest category
- Coding, 35.7 points apart on average over 5 shared benchmarks.
- Widest single gap
- Terminal-Bench 4.0 (Artificial Analysis run): Gemma 4 31B 0.0% against Muse Ember 40.9%, 40.9 points apart on a 0 to 100 scale.
- Output price
- Gemma 4 31B $0.40 against Muse Ember $0.50 per million output tokens, 1.3x apart.
- Context window
- Gemma 4 31B takes 262K tokens, Muse Ember 1.05M.
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 | Gemma 4 31B | Bars | Muse Ember | Ties |
|---|---|---|---|---|
| Coding | 0 | 5 | ||
| Reasoning | 0 | 2 | ||
| Knowledge | 0 | 1 | ||
| All shared boards | 0 | 8 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index05
| Benchmark | Gemma 4 31B | Muse Ember | Leader |
|---|---|---|---|
| LiveBench coding | 20.3% | Not measured | Only Gemma 4 31B measured |
| LMArena WebDev | 1370 | 1609 | Muse Ember |
| AA Coding Index | 43.4 | Not measured | Only Gemma 4 31B measured |
| Terminal-Bench 4 (Vals AI) | Not measured | 39.4% | Only Muse Ember measured |
| Vibe Code Bench (Vals AI) | Not measured | 83.7% | Only Muse Ember measured |
| SciCode | 45.5% | Not measured | Only Gemma 4 31B measured |
| Terminal-Bench Hard (Artificial Analysis run) | 36.4% | Not measured | Only Gemma 4 31B measured |
| Terminal-Bench 4.0 (Artificial Analysis run) | 0.0% | 40.9% | Muse Ember |
| FrontierCode 2.0 | 0.0% | 27.2% | Muse Ember |
| WeirdML | 52.3% | Not measured | Only Gemma 4 31B measured |
| ALE-Bench | 925.5 | Not measured | Only Gemma 4 31B measured |
| LMArena Text: coding | 1459 | Not measured | Only Gemma 4 31B measured |
| LMArena Text: software and IT | 1463 | Not measured | Only Gemma 4 31B measured |
| LMArena WebDev: React | 1362 | 1616 | Muse Ember |
| LMArena WebDev: HTML | 1380 | 1621 | Muse Ember |
| SciCode | 8.9% | Not measured | Only Gemma 4 31B measured |
| GameBench 2 | 35.1 | Not measured | Only Gemma 4 31B measured |
| Neither model has a result on the other 35 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | Gemma 4 31B | Muse Ember | Leader |
|---|---|---|---|
| AA Intelligence Index | 4.4 | Not measured | Only Gemma 4 31B measured |
| Epoch Capabilities Index | 144.3 | Not measured | Only Gemma 4 31B measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index9 boards, none shared
| Benchmark | Gemma 4 31B | Muse Ember | Leader |
|---|---|---|---|
| AA Agentic Index | 4.2 | Not measured | Only Gemma 4 31B measured |
| LiveBench research | 38.1% | Not measured | Only Gemma 4 31B measured |
| LiveBench browser | 0.0% | Not measured | Only Gemma 4 31B measured |
| LiveBench long agentic | 8.5% | Not measured | Only Gemma 4 31B measured |
| Tax Agent Bench (Vals AI) | Not measured | 38.2% | Only Muse Ember measured |
| Legal Research Bench (Vals AI) | Not measured | 49.0% | Only Muse Ember measured |
| Harvey's Legal Agent Benchmark (Vals AI) | Not measured | 25.0% | Only Muse Ember measured |
| τ²-Bench Telecom | 65.5% | Not measured | Only Gemma 4 31B measured |
| APEX-Agents | Not measured | 64.3% | Only Muse Ember measured |
| Neither model has a result on the other 35 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Gemma 4 31B | Muse Ember | Leader |
|---|---|---|---|
| LiveBench reasoning | 68.3% | Not measured | Only Gemma 4 31B measured |
| GPQA Diamond (Artificial Analysis run) | 85.7% | Not measured | Only Gemma 4 31B measured |
| Humanity's Last Exam (Artificial Analysis run) | 23.6% | Not measured | Only Gemma 4 31B measured |
| HLE-Diamond (Artificial Analysis run) | 7.2% | 25.1% | Muse Ember |
| CritPt v2, hard subset (Artificial Analysis run) | 4.0% | 39.0% | Muse Ember |
| GPQA Diamond (Epoch AI run) | 75.8% | Not measured | Only Gemma 4 31B measured |
| LMArena Text: hard prompts | 1447 | Not measured | Only Gemma 4 31B measured |
| LMArena Text: expert | 1465 | Not measured | Only Gemma 4 31B measured |
| LMArena Text: hard prompts in English | 1456 | Not measured | Only Gemma 4 31B measured |
| LMArena Vision: diagrams | 1286 | Not measured | Only Gemma 4 31B measured |
| LMArena Vision: homework | 1310 | Not measured | Only Gemma 4 31B measured |
| Kagi LLM Benchmark | 63.5% | Not measured | Only Gemma 4 31B measured |
| Neither model has a result on the other 14 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
| Benchmark | Gemma 4 31B | Muse Ember | Leader |
|---|---|---|---|
| OTIS Mock AIME | 73.3% | Not measured | Only Gemma 4 31B measured |
| LMArena Text: math | 1462 | Not measured | Only Gemma 4 31B measured |
| LMArena Text: mathematical work | 1464 | Not measured | Only Gemma 4 31B measured |
| Neither model has a result on the other 11 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Gemma 4 31B | Muse Ember | Leader |
|---|---|---|---|
| CaseLaw (Vals AI) | 52.6% | Not measured | Only Gemma 4 31B measured |
| MortgageTax (Vals AI) | 61.4% | Not measured | Only Gemma 4 31B measured |
| AA-Omniscience | -48.5 | 7.7 | Muse Ember |
| SimpleQA Verified | 10.4% | Not measured | Only Gemma 4 31B measured |
| LMArena Text: science | 1456 | Not measured | Only Gemma 4 31B measured |
| LMArena Text: medicine and healthcare | 1450 | Not measured | Only Gemma 4 31B measured |
| LMArena Text: legal and government | 1438 | Not measured | Only Gemma 4 31B measured |
| LMArena Text: business and finance | 1431 | Not measured | Only Gemma 4 31B measured |
| FACTS Benchmark Suite | 50.1% | Not measured | Only Gemma 4 31B measured |
| Neither model has a result on the other 12 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | Gemma 4 31B | Muse Ember | Leader |
|---|---|---|---|
| LiveBench design | 56.5% | Not measured | Only Gemma 4 31B measured |
| Neither model has a result on the other 8 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index33 boards, none shared
| Benchmark | Gemma 4 31B | Muse Ember | Leader |
|---|---|---|---|
| Vals Index | Not measured | 60.5% | Only Muse Ember measured |
| LiveBench data analysis | 53.3% | Not measured | Only Gemma 4 31B measured |
| SAGE (Vals AI) | 82.8% | Not measured | Only Gemma 4 31B measured |
| IFBench | 75.6% | Not measured | Only Gemma 4 31B measured |
| Long context reasoning (AA-LCR) | 69.7% | Not measured | Only Gemma 4 31B measured |
| GDPval-AA | 627 | Not measured | Only Gemma 4 31B measured |
| DTBench | 82.7% | Not measured | Only Gemma 4 31B measured |
| LMCA | 39.3% | Not measured | Only Gemma 4 31B measured |
| Surface Evolver Bench | 30.6% | Not measured | Only Gemma 4 31B measured |
| LMArena Text | 1443 | Not measured | Only Gemma 4 31B measured |
| LMArena Text: instruction following | 1433 | Not measured | Only Gemma 4 31B measured |
| LMArena Text: creative writing | 1415 | Not measured | Only Gemma 4 31B measured |
| LMArena Vision | 1279 | Not measured | Only Gemma 4 31B measured |
| LMArena Text: English | 1451 | Not measured | Only Gemma 4 31B measured |
| LMArena Text: non-English | 1430 | Not measured | Only Gemma 4 31B measured |
| LMArena Text: Chinese | 1476 | Not measured | Only Gemma 4 31B measured |
| LMArena Text: French | 1434 | Not measured | Only Gemma 4 31B measured |
| LMArena Text: Spanish | 1444 | Not measured | Only Gemma 4 31B measured |
| LMArena Text: Russian | 1460 | Not measured | Only Gemma 4 31B measured |
| LMArena Text: Polish | 1431 | Not measured | Only Gemma 4 31B measured |
| LMArena Text: multi-turn | 1452 | Not measured | Only Gemma 4 31B measured |
| LMArena Text: longer queries | 1445 | Not measured | Only Gemma 4 31B measured |
| LMArena Text: writing and language | 1431 | Not measured | Only Gemma 4 31B measured |
| LMArena Text: entertainment and media | 1405 | Not measured | Only Gemma 4 31B measured |
| LMArena Vision: English | 1272 | Not measured | Only Gemma 4 31B measured |
| LMArena Vision: Chinese | 1327 | Not measured | Only Gemma 4 31B measured |
| LMArena Vision: reading text | 1285 | Not measured | Only Gemma 4 31B measured |
| LMArena Vision: humor | 1280 | Not measured | Only Gemma 4 31B measured |
| LMArena Vision: captioning | 1209 | Not measured | Only Gemma 4 31B measured |
| LMArena Vision: recognizing things | 1227 | Not measured | Only Gemma 4 31B measured |
| LMArena Vision: creative writing | 1286 | Not measured | Only Gemma 4 31B measured |
| LMArena Document | 1434 | Not measured | Only Gemma 4 31B measured |
| EQ-Bench 4 | 1110 | Not measured | Only Gemma 4 31B measured |
| Neither model has a result on the other 16 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Gemma 4 31B | Muse Ember | 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
Gemma 4 31B costs less
Repository review
50K input + 3K output tokens
Muse Ember costs less
Agent loop
200K input + 10K output tokens
Muse Ember 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 | Google Gemma 4 31B | Meta Muse Ember |
|---|---|---|
| Maker | Meta | |
| Weights | Open weights | No public weights listed |
| Released | April 2, 2026 | November 9, 2026 |
| Context window | 262K | 1.05M |
| Input $/Mtok | $0.14 | $0.10 |
| Output $/Mtok | $0.40 | $0.50 |
| Coding index | 21.9 | 64.9 |
| Independent measurements behind it | 2 | 3 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Gemma 4 31B better than Muse Ember for coding?
Pick Muse Ember for coding: it scores 64.9 on the Vibe Coding Index against 21.9 for Gemma 4 31B. Pick Gemma 4 31B for output tokens 1.3x cheaper ($0.40 vs $0.50 per million).
Which is cheaper, Gemma 4 31B or Muse Ember?
Gemma 4 31B costs $0.14 per million input tokens and $0.40 per million output tokens; Muse Ember costs $0.10 and $0.50. Cost per solved task is known for neither of them.
Which has the bigger context window, Gemma 4 31B or Muse Ember?
Muse Ember, with 1.05M tokens against 262K.
How many benchmarks is the Gemma 4 31B vs Muse Ember comparison based on?
8 benchmarks have a result for both models as of November 14, 2026. Gemma 4 31B's coding index rests on 2 independent benchmarks and Muse Ember's on 3. Where only one model has a result, the page says so instead of naming a winner.