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Gemini 3.7 Flash (batch) vs Muse Ember

vs
Muse Ember

meta

40#157
Signal-by-Signal Comparison
SignalGemini 3.7 Flash (batch)DeltaMuse Ember
Capabilities
100
--
100
Pricing
98
-1
100
Context window size
96
--
96
Recency
100
--
100
Output Capacity
77
-18
96
Overall Result
0 wins
of 5
2 wins
Muse Ember wins 2 of 5 signals

Score History

Score History (14 data points)
Gemini 3.7 Flash (batch)Muse Ember
Gemini 3.7 Flash (batch)

40

current score

Leader

Tied

right now

Muse Ember

40

current score

LMMarketCap.com
Interactive Price Comparison
100Kcalls/month
1,000tokens (~1,333 chars)
500tokens (~667 chars)

Gemini 3.7 Flash (batch)

Google

Per request$0.001312
Daily$4.38
Monthly$131.25
Annual$1575.00

Muse Ember

meta

Best Value
Per request$0.000350
Daily$1.17
Monthly$35.00
Annual$420.00

Muse Ember saves you $96.25/month

That's $1155.00/year compared to Gemini 3.7 Flash (batch) at your current usage level of 100K calls/month.

73% cheaper
Choose Muse Ember for cost optimization

Gemini 3.7 Flash (batch) pricing:
Input:$0.38/M tokens
Output:$1.88/M tokens
Muse Ember pricing:
Input:$0.10/M tokens
Output:$0.50/M tokens
Tie
Gemini 3.7 Flash (batch)

Google

40

Composite Score

Tie
Muse Ember

meta

40

Composite Score

Signal-by-Signal Comparison
MetricGemini 3.7 Flash (batch)Muse EmberWinner
Overall Score
40
40
--
Rank#261#157
Muse Ember
Quality Rank#261#157
Muse Ember
Adoption Rank#261#157
Muse Ember
Parameters------
Context Window1049K1049K--
Pricing$0.38/$1.88/M$0.10/$0.50/M--
Signal Scores
Capabilities
100
100
Gemini 3.7 Flash (batch)
Pricing
98
100
Muse Ember
Context window size
96
96
Gemini 3.7 Flash (batch)
Recency
100
100
Gemini 3.7 Flash (batch)
Output Capacity
77
96
Muse Ember
Benchmark Interpretation

Our score (0-100) is driven by benchmark performance (90%) from Arena Elo ratings, MMLU, GPQA, HumanEval, SWE-bench, and 15+ standardized evaluations. Capabilities and context window serve as tiebreakers (10%). Learn more about our methodology.

Gemini 3.7 Flash (batch)Entry Level

Scores 40/100 (rank #261), placing it in the top 10% of all 290 models tracked.

Raw Quality0/100
Cost Efficiency0/100
Speed0/100
Muse EmberEntry Level

Scores 40/100 (rank #157), placing it in the top 46% of all 290 models tracked.

Raw Quality0/100
Cost Efficiency0/100
Speed0/100

With only a 0-point gap, these models are in the same performance tier. The practical difference in output quality is minimal - your choice should depend on pricing, latency requirements, and specific feature needs.

When to Use Each Model

Choose Gemini 3.7 Flash (batch) when you need:

  • Step-by-step reasoning and chain-of-thought problem solving

Choose Muse Ember when you need:

  • High-volume production workloads where API costs must be minimized
  • Step-by-step reasoning and chain-of-thought problem solving
Cost-Performance Analysis
Gemini 3.7 Flash (batch)
Input cost$0.38/M tokens
Output cost$1.88/M tokens
Cost per quality point$0.056
Est. monthly (1M tokens/day)$33.75
Muse EmberBest Value
Input cost$0.10/M tokens
Output cost$0.50/M tokens
Cost per quality point$0.015
Est. monthly (1M tokens/day)$9.00

Muse Ember offers 73% better value per quality point. At 1M tokens/day, you'd spend $9.00/month with Muse Ember vs $33.75/month with Gemini 3.7 Flash (batch) - a $24.75 monthly difference.

Latency & Speed
Gemini 3.7 Flash (batch)Faster
Speed score0/100
Muse Ember
Speed score0/100

Both models have comparable response speeds. For most applications, the latency difference is negligible.

When latency matters most: Interactive chatbots, IDE code completion, real-time translation, and user-facing applications where response time directly impacts experience. For batch processing, background summarization, or offline analysis, latency is less critical.

Example Use Cases

Code generation & review

Based on overall model capabilities and architecture for coding tasks like generating functions, debugging, and refactoring

Gemini 3.7 Flash (batch)

Customer support chatbot

Suitable for user-facing chat with competitive response times. Muse Ember also offers lower per-token costs for high-volume support

Gemini 3.7 Flash (batch)

Long document analysis

Larger context window (1049K tokens) can process longer documents, contracts, and research papers in a single pass

Gemini 3.7 Flash (batch)

Batch data extraction

Lower output pricing ($0.50/M) reduces costs when processing thousands of records daily

Muse Ember

Creative writing & content

Higher overall composite score (40/100) correlates with better nuance, coherence, and style in long-form content

Gemini 3.7 Flash (batch)

Image understanding & OCR

Supports vision input - can analyze screenshots, diagrams, photos, and scanned documents directly

Gemini 3.7 Flash (batch)
Which Should You Choose?
Our recommendation:
Gemini 3.7 Flash (batch)

Gemini 3.7 Flash (batch) and Muse Ember are extremely close in overall performance (only 0 points apart). Your best choice depends entirely on which specific strengths matter most for your use case.

by Google

  • Choose for Quality - Marginally better benchmark scores; both are excellent
  • Choose for Reliability - Higher uptime and faster response speeds
  • Choose for Prototyping - Stronger community support and better developer experience
  • Choose for Production - Wider enterprise adoption and proven at scale

by meta

  • Choose for Cost - 73% lower pricing; better value at scale
Capability Comparison
CapabilityGemini 3.7 Flash (batch)Muse Ember
Vision (Image Input)
Function Calling
Streaming
JSON Mode
Reasoning
Web Search
Image Output
Monthly Cost Calculator
1,000tokens (600 in / 400 out)
100requests/day (3,000/month)

Gemini 3.7 Flash (batch)

Google

$2.92
estimated monthly cost

Muse Ember

meta

Best Value
$0.7800
estimated monthly cost

Muse Ember saves you $2.15/month

That's 73% cheaper than Gemini 3.7 Flash (batch) at 1,000 tokens/request and 100 requests/day.

Assumes 60% input / 40% output token ratio per request. Actual costs may vary based on your usage pattern.

Parameters & Context
ParameterGemini 3.7 Flash (batch)Muse Ember
Context Window1.0M1.0M
Max Output Tokens65,536943,718
Open SourceNoNo
CreatedAug 13, 2026Nov 9, 2026
Last updated: 27m ago

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