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Muse Ember vs Qwen3.8 Max (0902) (batch)

Muse Ember

meta

40#147
vs
Signal-by-Signal Comparison
SignalMuse EmberDeltaQwen3.8 Max (0902) (batch)
Capabilities
100
+17
83
Pricing
100
+3
97
Context window size
96
+10
86
Recency
100
--
100
Output Capacity
96
+14
82
Overall Result
4 wins
of 5
0 wins
Muse Ember wins 4 of 5 signals

Score History Unavailable

Not enough historical data to show a comparison chart. Score history is recorded weekly and will be available after at least two data points are collected.

40

Muse Ember

vs

40

Qwen3.8 Max (0902) (batch)

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

Muse Ember

meta

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

Qwen3.8 Max (0902) (batch)

Alibaba

Per request$0.002875
Daily$9.58
Monthly$287.50
Annual$3450.00

Muse Ember saves you $252.50/month

That's $3030.00/year compared to Qwen3.8 Max (0902) (batch) at your current usage level of 100K calls/month.

88% cheaper
Choose Muse Ember for cost optimization

Muse Ember pricing:
Input:$0.10/M tokens
Output:$0.50/M tokens
Qwen3.8 Max (0902) (batch) pricing:
Input:$1.15/M tokens
Output:$3.45/M tokens
Tie
Muse Ember

meta

40

Composite Score

Tie
Qwen3.8 Max (0902) (batch)

Alibaba

40

Composite Score

Signal-by-Signal Comparison
MetricMuse EmberQwen3.8 Max (0902) (batch)Winner
Overall Score
40
40
--
Rank#147#226
Muse Ember
Quality Rank#147#226
Muse Ember
Adoption Rank#147#226
Muse Ember
Parameters------
Context Window1049K262K
Muse Ember
Pricing$0.10/$0.50/M$1.15/$3.45/M--
Signal Scores
Capabilities
100
83
Muse Ember
Pricing
100
97
Muse Ember
Context window size
96
86
Muse Ember
Recency
100
100
Muse Ember
Output Capacity
96
82
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.

Muse EmberEntry Level

Scores 40/100 (rank #147), placing it in the top 50% of all 290 models tracked.

Raw Quality0/100
Cost Efficiency0/100
Speed0/100
Qwen3.8 Max (0902) (batch)Entry Level

Scores 40/100 (rank #226), placing it in the top 22% 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 Muse Ember when you need:

  • High-volume production workloads where API costs must be minimized
  • Processing long documents or large codebases (1049K token context)
  • Step-by-step reasoning and chain-of-thought problem solving

Choose Qwen3.8 Max (0902) (batch) when you need:

  • Step-by-step reasoning and chain-of-thought problem solving
Cost-Performance Analysis
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
Qwen3.8 Max (0902) (batch)
Input cost$1.15/M tokens
Output cost$3.45/M tokens
Cost per quality point$0.115
Est. monthly (1M tokens/day)$69.00

Muse Ember offers 87% better value per quality point. At 1M tokens/day, you'd spend $9.00/month with Muse Ember vs $69.00/month with Qwen3.8 Max (0902) (batch) - a $60.00 monthly difference.

Latency & Speed
Muse EmberFaster
Speed score0/100
Qwen3.8 Max (0902) (batch)
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

Muse Ember

Customer support chatbot

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

Muse Ember

Long document analysis

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

Muse Ember

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

Muse Ember

Image understanding & OCR

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

Muse Ember
Which Should You Choose?
Our recommendation:
Muse Ember

Muse Ember and Qwen3.8 Max (0902) (batch) 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.

Muse Ember
Recommended

by meta

  • Choose for Quality - Marginally better benchmark scores; both are excellent
  • Choose for Cost - 87% lower pricing; better value at scale
  • 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 Alibaba

Consider for specialized use cases.

Capability Comparison
CapabilityMuse EmberQwen3.8 Max (0902) (batch)
Vision (Image Input)
Function Calling
Streaming
JSON Mode
Reasoning
Web Searchdiffers
Image Output
Monthly Cost Calculator
1,000tokens (600 in / 400 out)
100requests/day (3,000/month)

Muse Ember

meta

Best Value
$0.7800
estimated monthly cost

Qwen3.8 Max (0902) (batch)

Alibaba

$6.21
estimated monthly cost

Muse Ember saves you $5.43/month

That's 87% cheaper than Qwen3.8 Max (0902) (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
ParameterMuse EmberQwen3.8 Max (0902) (batch)
Context Window1.0M262K
Max Output Tokens943,718131,072
Open SourceNoNo
CreatedNov 9, 2026Sep 3, 2026
Last updated: 30m ago

相关对比

Muse Ember vs Qwen3.8 Max (0902) (batch) (2026) | LM Market Cap