Enter opens the highlighted result. Esc closes.

Gemini 3.7 Flash vs Muse Ember

Muse Ember leads Gemini 3.7 Flash on coding, 64.9 to 53.9 on the Vibe Coding Index, and Muse Ember costs 7.5x less per output token ($0.50 vs $3.75 per million). Updated November 14, 2026; 9 benchmarks have a result for both.

Gemini 3.7 FlashGoogle
Coding
53.9
Overall
66.3
Output $/M
$3.75
1
Muse EmberMeta
Coding
64.9
Overall
No data
Output $/M
$0.50
8
vs boards won of 9 shared

Gemini 3.7 Flash or Muse Ember: which to pick

Pick Muse Ember for coding: it scores 64.9 on the Vibe Coding Index against 53.9 for Gemini 3.7 Flash, though on 3 benchmarks against 5.

Pick Gemini 3.7 Flash for work measured by APEX-Agents, where it leads.

Shared results
9
Gemini 3.7 Flash only
104
Muse Ember only
6
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.

At a glance

Coding index
Gemini 3.7 Flash 53.9 from 5 benchmarks, Muse Ember 64.9 from 3 benchmarks.
Widest category
Coding, 14.0 points apart on average over 6 shared benchmarks.
Widest single gap
Terminal-Bench 4 (Vals AI): Gemini 3.7 Flash 12.1% against Muse Ember 39.4%, 36.4 points apart on a 0 to 100 scale.
Output price
Gemini 3.7 Flash $3.75 against Muse Ember $0.50 per million output tokens, 7.5x apart.
Context window
Both take 1.05M 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.

Boards won, where both have a result
CategoryGemini 3.7 FlashBarsMuse EmberTies
Coding06
Agentic work12
All shared boards18
CodingLike-for-likeSix of these boards feed the Vibe Coding Index06
Coding benchmarks for Gemini 3.7 Flash and Muse Ember
BenchmarkGemini 3.7 FlashMuse EmberLeader
LMArena WebDev15881609Muse Ember
AA Coding Index76.1Not measuredOnly Gemini 3.7 Flash measured
LiveCodeBench (Vals AI)88.7%Not measuredOnly Gemini 3.7 Flash measured
SWE-bench Verified (Vals AI)80.8%Not measuredOnly Gemini 3.7 Flash measured
Terminal-Bench 4 (Vals AI)12.1%39.4%Muse Ember
Vibe Code Bench (Vals AI)70.4%83.7%Muse Ember
Code migration (Vals AI)34.8%Not measuredOnly Gemini 3.7 Flash measured
ProgramBench (Vals AI)0.0%Not measuredOnly Gemini 3.7 Flash measured
IOI (Vals AI)67.8%Not measuredOnly Gemini 3.7 Flash measured
Terminal-Bench 2.1 (Vals AI)77.5%Not measuredOnly Gemini 3.7 Flash measured
SkillsBench (Vals AI)65.9%Not measuredOnly Gemini 3.7 Flash measured
CyberBench (Vals AI)43.8%Not measuredOnly Gemini 3.7 Flash measured
SciCode59.8%Not measuredOnly Gemini 3.7 Flash measured
Terminal-Bench 4.0 (Artificial Analysis run)13.6%40.9%Muse Ember
FrontierCode 2.0Not measured27.2%Only Muse Ember measured
FrontierCode43.6%Not measuredOnly Gemini 3.7 Flash measured
FrontierSWE20.3%Not measuredOnly Gemini 3.7 Flash measured
MirrorCode41.1%Not measuredOnly Gemini 3.7 Flash measured
ALE-Bench904.3Not measuredOnly Gemini 3.7 Flash measured
LMArena Text: coding1500Not measuredOnly Gemini 3.7 Flash measured
LMArena Text: software and IT1500Not measuredOnly Gemini 3.7 Flash measured
LMArena WebDev: React15831616Muse Ember
LMArena WebDev: HTML15931621Muse Ember
LMArena WebDev: from an image1600Not measuredOnly Gemini 3.7 Flash measured
SciCode13.8%Not measuredOnly Gemini 3.7 Flash measured
Terminal-Bench 4.011.2%Not measuredOnly Gemini 3.7 Flash measured
ProgramBench0.0%Not measuredOnly Gemini 3.7 Flash measured
Neither model has a result on the other 25 boards here
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
Intelligence benchmarks for Gemini 3.7 Flash and Muse Ember
BenchmarkGemini 3.7 FlashMuse EmberLeader
Epoch Capabilities Index158.4Not measuredOnly Gemini 3.7 Flash measured
Neither model has a result on the other 1 board here
Agentic workLike-for-likePublic boards, shown as published, kept out of the index12
Agentic work benchmarks for Gemini 3.7 Flash and Muse Ember
BenchmarkGemini 3.7 FlashMuse EmberLeader
AA Agentic Index35.2Not measuredOnly Gemini 3.7 Flash measured
Design Arena: agents building web apps1201Not measuredOnly Gemini 3.7 Flash measured
Design Arena: agents building full-stack apps1185Not measuredOnly Gemini 3.7 Flash measured
Design Arena: agents building mobile apps1226Not measuredOnly Gemini 3.7 Flash measured
Design Arena: agents building Android apps1233Not measuredOnly Gemini 3.7 Flash measured
Design Arena: agents building Godot games1236Not measuredOnly Gemini 3.7 Flash measured
Design Arena: agents building games1177Not measuredOnly Gemini 3.7 Flash measured
Design Arena: PowerPoint slides1069Not measuredOnly Gemini 3.7 Flash measured
Design Arena: spreadsheets1014Not measuredOnly Gemini 3.7 Flash measured
SREBench (Vals AI)4.6%Not measuredOnly Gemini 3.7 Flash measured
Finance Agent (Vals AI)59.0%Not measuredOnly Gemini 3.7 Flash measured
Tax Agent Bench (Vals AI)22.8%38.2%Muse Ember
Legal Research Bench (Vals AI)34.6%49.0%Muse Ember
Harvey's Legal Agent Benchmark (Vals AI)Not measured25.0%Only Muse Ember measured
Excel Modeling Benchmark (Vals AI)71.3%Not measuredOnly Gemini 3.7 Flash measured
Terminal-Bench-Science (Vals AI)7.1%Not measuredOnly Gemini 3.7 Flash measured
APEX-Agents67.8%64.3%Gemini 3.7 Flash
Remote Labor Index5.0%Not measuredOnly Gemini 3.7 Flash measured
Neither model has a result on the other 26 boards here
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index16 boards, none shared
Reasoning benchmarks for Gemini 3.7 Flash and Muse Ember
BenchmarkGemini 3.7 FlashMuse EmberLeader
GPQA Diamond93.9%Not measuredOnly Gemini 3.7 Flash measured
MMMU Pro (Vals AI)89.0%Not measuredOnly Gemini 3.7 Flash measured
GPQA Diamond (Artificial Analysis run)94.5%Not measuredOnly Gemini 3.7 Flash measured
Humanity's Last Exam (Artificial Analysis run)47.9%Not measuredOnly Gemini 3.7 Flash measured
HLE-Diamond (Artificial Analysis run)Not measured25.1%Only Muse Ember measured
CritPt v2, hard subset (Artificial Analysis run)Not measured39.0%Only Muse Ember measured
GPQA Diamond (Epoch AI run)94.8%Not measuredOnly Gemini 3.7 Flash measured
ARC-AGI95.5%Not measuredOnly Gemini 3.7 Flash measured
ARC-AGI-284.6%Not measuredOnly Gemini 3.7 Flash measured
Chess puzzles66.0%Not measuredOnly Gemini 3.7 Flash measured
Mystery game puzzles37.0%Not measuredOnly Gemini 3.7 Flash measured
LMArena Text: hard prompts1498Not measuredOnly Gemini 3.7 Flash measured
LMArena Text: expert1515Not measuredOnly Gemini 3.7 Flash measured
LMArena Text: hard prompts in English1488Not measuredOnly Gemini 3.7 Flash measured
LMArena Vision: diagrams1329Not measuredOnly Gemini 3.7 Flash measured
LMArena Vision: homework1325Not measuredOnly Gemini 3.7 Flash measured
Neither model has a result on the other 10 boards here
MathDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
Math benchmarks for Gemini 3.7 Flash and Muse Ember
BenchmarkGemini 3.7 FlashMuse EmberLeader
OTIS Mock AIME97.2%Not measuredOnly Gemini 3.7 Flash measured
FrontierMath, tiers 1 to 371.6%Not measuredOnly Gemini 3.7 Flash measured
FrontierMath, tier 436.6%Not measuredOnly Gemini 3.7 Flash measured
ProofBench58.0%Not measuredOnly Gemini 3.7 Flash measured
LMArena Text: math1506Not measuredOnly Gemini 3.7 Flash measured
LMArena Text: mathematical work1500Not measuredOnly Gemini 3.7 Flash measured
MathArena23.9%Not measuredOnly Gemini 3.7 Flash measured
Neither model has a result on the other 7 boards here
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index11 boards, none shared
Knowledge benchmarks for Gemini 3.7 Flash and Muse Ember
BenchmarkGemini 3.7 FlashMuse EmberLeader
MMLU Pro90.1%Not measuredOnly Gemini 3.7 Flash measured
LegalBench (Vals AI)87.3%Not measuredOnly Gemini 3.7 Flash measured
TaxEval (Vals AI)74.7%Not measuredOnly Gemini 3.7 Flash measured
MortgageTax (Vals AI)66.7%Not measuredOnly Gemini 3.7 Flash measured
MedCode (Vals AI)53.4%Not measuredOnly Gemini 3.7 Flash measured
AA-OmniscienceNot measured7.7Only Muse Ember measured
SimpleQA Verified69.2%Not measuredOnly Gemini 3.7 Flash measured
LMArena Text: science1511Not measuredOnly Gemini 3.7 Flash measured
LMArena Text: medicine and healthcare1499Not measuredOnly Gemini 3.7 Flash measured
LMArena Text: legal and government1498Not measuredOnly Gemini 3.7 Flash measured
LMArena Text: business and finance1481Not measuredOnly Gemini 3.7 Flash measured
Neither model has a result on the other 10 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
Web design benchmarks for Gemini 3.7 Flash and Muse Ember
BenchmarkGemini 3.7 FlashMuse EmberLeader
Design Arena: websites1295Not measuredOnly Gemini 3.7 Flash measured
Design Arena: UI components1287Not measuredOnly Gemini 3.7 Flash measured
Design Arena: game dev1312Not measuredOnly Gemini 3.7 Flash measured
Design Arena: data viz1308Not measuredOnly Gemini 3.7 Flash measured
Design Arena: 3D1287Not measuredOnly Gemini 3.7 Flash measured
Design Arena: all code categories1298Not measuredOnly Gemini 3.7 Flash measured
Design Arena: SVG1278Not measuredOnly Gemini 3.7 Flash measured
Design Arena: ASCII art1267Not measuredOnly Gemini 3.7 Flash measured
Neither model has a result on the other 1 board here
GeneralDirectional onlyPublic boards, shown as published, kept out of the index31 boards, none shared
General benchmarks for Gemini 3.7 Flash and Muse Ember
BenchmarkGemini 3.7 FlashMuse EmberLeader
Vals IndexNot measured60.5%Only Muse Ember measured
MedScribe (Vals AI)83.9%Not measuredOnly Gemini 3.7 Flash measured
Long context reasoning (AA-LCR)83.0%Not measuredOnly Gemini 3.7 Flash measured
GDPval-AA1404Not measuredOnly Gemini 3.7 Flash measured
DTBench96.8%Not measuredOnly Gemini 3.7 Flash measured
LMCA50.4%Not measuredOnly Gemini 3.7 Flash measured
Furniture assembly26.7%Not measuredOnly Gemini 3.7 Flash measured
LMArena Text1489Not measuredOnly Gemini 3.7 Flash measured
LMArena Text: instruction following1485Not measuredOnly Gemini 3.7 Flash measured
LMArena Text: creative writing1485Not measuredOnly Gemini 3.7 Flash measured
LMArena Vision1313Not measuredOnly Gemini 3.7 Flash measured
LMArena Text: English1484Not measuredOnly Gemini 3.7 Flash measured
LMArena Text: non-English1486Not measuredOnly Gemini 3.7 Flash measured
LMArena Text: Chinese1553Not measuredOnly Gemini 3.7 Flash measured
LMArena Text: German1514Not measuredOnly Gemini 3.7 Flash measured
LMArena Text: Japanese1515Not measuredOnly Gemini 3.7 Flash measured
LMArena Text: Korean1483Not measuredOnly Gemini 3.7 Flash measured
LMArena Text: French1494Not measuredOnly Gemini 3.7 Flash measured
LMArena Text: Spanish1484Not measuredOnly Gemini 3.7 Flash measured
LMArena Text: Russian1513Not measuredOnly Gemini 3.7 Flash measured
LMArena Text: Polish1507Not measuredOnly Gemini 3.7 Flash measured
LMArena Text: multi-turn1487Not measuredOnly Gemini 3.7 Flash measured
LMArena Text: longer queries1494Not measuredOnly Gemini 3.7 Flash measured
LMArena Text: writing and language1489Not measuredOnly Gemini 3.7 Flash measured
LMArena Text: entertainment and media1474Not measuredOnly Gemini 3.7 Flash measured
LMArena Vision: English1309Not measuredOnly Gemini 3.7 Flash measured
LMArena Vision: Chinese1388Not measuredOnly Gemini 3.7 Flash measured
LMArena Vision: reading text1321Not measuredOnly Gemini 3.7 Flash measured
LMArena Vision: humor1300Not measuredOnly Gemini 3.7 Flash measured
LMArena Vision: creative writing1320Not measuredOnly Gemini 3.7 Flash measured
LMArena Document1476Not measuredOnly Gemini 3.7 Flash measured
Neither model has a result on the other 18 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Gemini 3.7 Flash and Muse Ember
BenchmarkGemini 3.7 FlashMuse EmberLeader
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

Gemini 3.7 Flash$0.0026Fits in one request
Muse Ember$0.0003Fits in one request

Muse Ember costs less

Repository review

50K input + 3K output tokens

Gemini 3.7 Flash$0.049Fits in one request
Muse Ember$0.0065Fits in one request

Muse Ember costs less

Agent loop

200K input + 10K output tokens

Gemini 3.7 Flash$0.188Fits in one request
Muse Ember$0.025Fits in one request

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.

Specifications of Gemini 3.7 Flash and Muse Ember
SpecificationGoogle Gemini 3.7 FlashMeta Muse Ember
MakerGoogleMeta
WeightsNo public weights listedNo public weights listed
ReleasedAugust 13, 2026November 9, 2026
Context window1.05M1.05M
Input $/Mtok$0.75$0.10
Output $/Mtok$3.75$0.50
Coding index53.964.9
Independent measurements behind it53
Cost per solved task$1.78Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Gemini 3.7 Flash better than Muse Ember for coding?

Pick Muse Ember for coding: it scores 64.9 on the Vibe Coding Index against 53.9 for Gemini 3.7 Flash, though on 3 benchmarks against 5. Pick Gemini 3.7 Flash for work measured by APEX-Agents, where it leads.

Which is cheaper, Gemini 3.7 Flash or Muse Ember?

Gemini 3.7 Flash costs $0.75 per million input tokens and $3.75 per million output tokens; Muse Ember costs $0.10 and $0.50. Cost per solved task is known for Gemini 3.7 Flash only.

Which has the bigger context window, Gemini 3.7 Flash or Muse Ember?

Neither: both take 1.05M tokens.

How many benchmarks is the Gemini 3.7 Flash vs Muse Ember comparison based on?

9 benchmarks have a result for both models as of November 14, 2026. Gemini 3.7 Flash's coding index rests on 5 independent benchmarks and Muse Ember's on 3. Where only one model has a result, the page says so instead of naming a winner.

Compare next

Embed this comparison on your site

Free under CC BY 4.0, while the source link stays visible. Preview the frame · Terms and other embeds

<iframe src="https://llmbenchmark.ai/embed/compare/gemini-3-7-flash-vs-meta-muse-ember" title="Gemini 3.7 Flash vs Muse Ember, LLMBenchmark.ai" width="100%" height="360" style="border:0;max-width:100%" loading="lazy"></iframe>
<p style="font:13px/1.4 sans-serif;margin:6px 0 0">Source: <a href="https://llmbenchmark.ai/compare/gemini-3-7-flash-vs-meta-muse-ember">LLMBenchmark.ai, Gemini 3.7 Flash vs Muse Ember</a></p>