Compare · ModelsLive · 2 picked · head to head
gpt-oss-120b (free) vs Muse Spark
Side by side · benchmarks, pricing, and signals you can act on.
Winner summary
Muse Spark wins on 3/3 benchmarks
Muse Spark wins 3 of 3 shared benchmarks. Leads in speed.
Category leads
speed·Muse Spark
Hype vs Reality
Attention vs performance
gpt-oss-120b (free)
#22 by perf·no signal
Muse Spark
#47 by perf·no signal
Vendor risk
Who is behind the model
OpenAI
$840.0B·Tier 1
U
Unknown
private · undisclosed
Head to head
3 benchmarks · 2 models
gpt-oss-120b (free)Muse Spark
Artificial Analysis · Agentic Index
Muse Spark leads by +24.1
Artificial Analysis Agentic Index · a composite score measuring how well a model performs in agentic workflows · multi-step tool use, planning, error recovery, and autonomous task completion. Aggregates results from multiple agentic benchmarks including SWE-bench, tool-use tests, and planning evaluations. The canonical single-number metric for "how good is this model as an agent?"
gpt-oss-120b (free)
37.9
Muse Spark
62.0
Artificial Analysis · Coding Index
Muse Spark leads by +18.8
Artificial Analysis Coding Index · a composite score that aggregates performance across multiple coding benchmarks into a single index. Tracks code generation quality, debugging ability, multi-language competence, and real-world software engineering tasks. Used by Artificial Analysis to rank model coding capability in a normalized, comparable format. Useful for developers choosing between models for coding-heavy workloads.
gpt-oss-120b (free)
28.6
Muse Spark
47.5
Artificial Analysis · Quality Index
Muse Spark leads by +18.9
gpt-oss-120b (free)
33.3
Muse Spark
52.1
Full benchmark table
| Benchmark | gpt-oss-120b (free) | Muse Spark |
|---|---|---|
Artificial Analysis · Agentic Index Artificial Analysis Agentic Index · a composite score measuring how well a model performs in agentic workflows · multi-step tool use, planning, error recovery, and autonomous task completion. Aggregates results from multiple agentic benchmarks including SWE-bench, tool-use tests, and planning evaluations. The canonical single-number metric for "how good is this model as an agent?" | 37.9 | 62.0 |
Artificial Analysis · Coding Index Artificial Analysis Coding Index · a composite score that aggregates performance across multiple coding benchmarks into a single index. Tracks code generation quality, debugging ability, multi-language competence, and real-world software engineering tasks. Used by Artificial Analysis to rank model coding capability in a normalized, comparable format. Useful for developers choosing between models for coding-heavy workloads. | 28.6 | 47.5 |
Artificial Analysis · Quality Index | 33.3 | 52.1 |
Pricing · per 1M tokens · projected $/mo at 10M tokens
| Model | Input | Output | Context | Projected $/mo |
|---|---|---|---|---|
| $0.00 | $0.00 | 131K tokens (~66 books) | — | |
U Muse Spark | — | — | — | — |
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