Meta•Rank #67NEW

Muse Ember

Proprietarygeneralfastbudgetmultimodal

Leaderboard Score

44.8

Scale: 0 - 100

Throughput Speed

185 tps

Context Window

API Pricing / 1M

.20

Parameter Scale

Proprietary

Monthly API Cost Calculator

Muse Ember rates: $0.1/1M input • $0.5/1M output. Pick a workload preset or enter your own token volumes.

Monthly input (M tokens)Monthly output (M tokens)

Same workload on published-rate alternatives

Ling 3.1 Flash (InclusionAI)

Qwen3.8-Flash-Next (Qwen / Alibaba)

Open the comparison engine →

Estimates use listed API rates at time of writing; providers may differ in caching discounts, rate limits, and batching pricing.

Sourced AI Radar & Benchmarks•8 Evaluated Metrics

Capability Radar & Benchmark Scores

Multi-Axis Capability Radar

Comparing Muse Ember against Frontier Top 10 & Open-Source average

0 - 100 Scale

Muse Ember

Frontier Top 10 Avg

Open-Source Avg

Performance Vectors

Where Muse Ember Leads

Coding & SWETop 10: 79.2% • OS: 51.6%

46.2%-33.0% vs Top 10

Reasoning & MathTop 10: 94.6% • OS: 54.3%

76.5%-18.1% vs Top 10

Agent & Tool AutomationTop 10: 80.3% • OS: 37.4%

44.0%-36.3% vs Top 10

Terminal & CLI ExecutionTop 10: 63.5% • OS: 45.8%

38.0%-25.5% vs Top 10

MMLU & Knowledge QATop 10: 50% • OS: 86.7%

56.0%+6.0% vs Top 10

Cyber & Security ExploitsTop 10: 87.3% • OS: 81.2%

42.6%-44.7% vs Top 10

All Verified Benchmark Evaluations

Direct Pass@1 and resolution rates across standardized evaluations.

OverallCodingReasoningAgenticTerminal

Featured Compute Platform

Run Benchmarks on Dedicated AI Clusters

Zero-cold-start inference endpoints with dedicated GPU instances.

Compare With Alternatives →

Executive Analysis & Verdict

Muse Ember by Meta is an ultra-fast, budget multimodal agent worker model scoring 44.8 overall, matching Claude Haiku 5.5 on the AA Index v5 (36.0) at one-third of the inference cost ($0.10 / $0.50 per 1M).

Key Strengths & Highlights

•Unmatched economic efficiency at $0.10 per 1M input tokens and $0.50 per 1M output tokens
•Matches Claude Haiku 5.5 on the Artificial Analysis Index v5 (36.0) while costing 67% less
•Expansive 1M context window with 512K output token capacity and 185 tokens/sec throughput

Limitations & Considerations

•Complex multi-step reasoning requires orchestration alongside larger Muse Wonder models

Recommended Workflows

High-volume agentic tool calling, sub-agent routing, automated document extraction, and rapid code review

Architectural Overview & Capability Profile

Muse Ember is Meta AI’s smallest and most cost-effective multimodal foundation model, engineered specifically to serve as a high-speed “worker” sub-agent in production multi-agent architectures. Designed to handle high-frequency, repetitive tasks such as JSON routing, data extraction, test execution, and document parsing without incurring the latency and cost of frontier models, Muse Ember scores an overall 44.8 / 100 on RankLLMs.

Despite its lightweight footprint, Muse Ember features an expansive 1,000,000-token context window with a 512,000-token maximum output limit, natively processing text, high-resolution imagery, audio, and video streams at a rapid 185 tokens per second.

Benchmark Performance & Cost-per-Task Comparison

Evaluations by Meta and independent benchmark testing from Artificial Analysis demonstrate notable value per dollar:

Artificial Analysis Intelligence Index v5.0:
- Scores 36.0, matching Claude Haiku 5.5 (36.2) and substantially outperforming GPT-6 Luna (28.0).
Cost-per-Task Efficiency:
- Resolves standardized agentic tasks at approximately $0.136 per task, compared to ~$0.411 for Claude Haiku 5.5—delivering roughly a 67% reduction in operational cost.
Latency & Execution Speed:
- In benchmark coding quests, Muse Ember achieves a p95 latency of just 2.2 seconds while utilizing 36% to 48% fewer output tokens through compact, direct reasoning.

API Pricing & Token Economics

Muse Ember is available via the Meta Model API and partner aggregators:

Input Tokens: $0.10 per 1M tokens.
Output Tokens: $0.50 per 1M tokens.
Cached Input: $0.01 per 1M tokens.

Frequently Asked Questions About Muse Ember

What is Muse Ember and who developed it?↓

Muse Ember is a proprietary large language model developed by Meta. It ranks #67 on the RankLLMs composite leaderboard, ahead of 38% of the 104 models we track, with an overall score of 44.8 / 100.

Can Muse Ember handle very long documents and codebases?↓

Muse Ember supports a 1.0M-token input context window and generates about 185 tps tokens per second in our reference measurements and which is enough to hold entire repositories, long transcripts, or multi-document research sets in a single session..

Why is Muse Ember priced so far below its peers?↓

Muse Ember is cheaper than 79% of the priced models we track at .20 per 1M tokens, while keeping competitive benchmark scores - which is why it rates well on cost per solved task, not just per token.

What is Muse Ember best at?↓

Muse Ember is strongest in Unmatched economic efficiency at $0.10 per 1M input tokens and $0.50 per 1M output tokens; Matches Claude Haiku 5.5 on the Artificial Analysis Index v5 (36.0) while costing 67% less; Expansive 1M context window with 512K output token capacity and 185 tokens/sec throughput. Full pillar-by-pillar numbers are in the benchmark tables above.

What should you watch out for with Muse Ember?↓

Known trade-offs include: Complex multi-step reasoning requires orchestration alongside larger Muse Wonder models. Weigh these against the strengths above for your specific workload.