readable AI benchmarks (simplified)
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Muse Spark 1.3 (xhigh)
Muse Spark 1.3 (xhigh) has a Quality Score of 69.6, ranking 20th among 277 scored models. Per 1M tokens, pricing is $1.25 input, $4.25 output, and $0.150 cached input. It accepts text, image, and video input, outputs text, and has a 1M token context window. Its Reliability Score is 61.6, ranking 24th among 277 scored models, above average (total average: 34.6). Its Value Score is 51.7, high compared with the total Value average of 28.7.
Quality Score69.6coverage 91.2%: missing Epoch General ECI, CursorBench 3.2 and DeepSWE v1.1
Value Score51.7
Reliability61.6
Cache Discount88%
Model specification
- Reasoning
- reasoning
- Input modalities
- text, image, video
- Output modalities
- text
- Context window
- 1M tokens
- Weights
- closed weights
Token prices USD per 1M tokens
- Input
- $1.25
- Output
- $4.25
- Cached Input
- $0.150
- Cached Output
- not available
- Cost per task
- $0.547
Capability
- Intelligence
- 60.8
- Coding
- 76.5
- Agentic
- 56.1
- Omniscience
- 23.1
- Correct
- 41.5%
- Blended price
- $0.780
Answer outcomes
Attempt rate: 59.9%
Correct 41.5%Incorrect 18.4%Abstained 40.1%
Artificial Analysis benchmarks
- GDPval-AA v2
- 60%
- τ³-Banking
- 47%
- Terminal-Bench v2.1
- 85%
- SciCode
- 59%
- Humanity’s Last Exam
- 47%
- GPQA Diamond
- 94%
- CritPt
- 26%
- AA-Omniscience
- 62%
- AA-LCR
- 79%
Similar models
- Muse Spark 1.3 (max)MetaQuality Score 71.5Value Score not available
- Muse Spark 1.2 (xhigh)MetaQuality Score 67.8Value Score 50.0
- Muse Glimmer (high)MetaQuality Score 34.2Value Score 34.0
- Llama 3.1 Instruct 405BMetaQuality Score 21.4Value Score not available
- Llama 4 MaverickMetaQuality Score 17.6Value Score 16.9
- Llama 3.3 Instruct 70BMetaQuality Score 12.6Value Score 10.4