Model comparison
GPT-5.1-Codex vs Muse Spark
Head-to-head evidence from 13 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: GPT-5.1-Codex #99 (Estimated); Muse Spark #13 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. GPT-5.1-Codex and Muse Spark share 13 comparable benchmark results. 0 of 8 categories are comparable. 3 results are unique to GPT-5.1-Codex; 26 to Muse Spark.
Updated July 23, 2026- Shared results
- 13
- GPT-5.1-Codex only
- 3
- Muse Spark only
- 26
- Comparable categories
- 0 / 8
Benchmark data for GPT-5.1-Codex and Muse Spark is coming soon on BenchLM.
Confidence note. This is a partial-evidence comparison with 13 shared benchmark results across 6 evidence categories; 0 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
BenchLM has partial data for these models, but not enough overlapping benchmark coverage to produce a fair score-level comparison yet.
GPT-5.1-Codex has the larger context window at 400K, compared with 262K for Muse Spark.
Category breakdown
Exact category averages are shown below. Not measured means BenchLM does not have enough sourced public coverage for that model and category.
| Category | GPT-5.1-Codex | Δ | Muse Spark |
|---|---|---|---|
| Agentic | GPT-5.1-CodexNot measured | MarginNo overlap | Muse Spark59.0 |
| Coding | GPT-5.1-CodexNot measured | MarginNo overlap | Muse Spark67.8 |
| Reasoning | GPT-5.1-CodexNot measured | MarginNo overlap | Muse Spark42.5 |
| Knowledge | GPT-5.1-CodexNot measured | MarginNo overlap | Muse Spark50.4 |
| Math | GPT-5.1-CodexNot measured | MarginNo overlap | Muse Spark32.9 |
| Multimodal | GPT-5.1-CodexNot measured | MarginNo overlap | Muse Spark82.5 |
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | GPT-5.1-Codex | Muse Spark | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GPT-5.1-CodexNot available | Muse SparkNot available | A complete price comparison is not available. |
| Generation speedtokens per second | GPT-5.1-CodexNot available | Muse SparkNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | GPT-5.1-CodexNot available | Muse SparkNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | GPT-5.1-Codex400K | Muse Spark262K | GPT-5.1-Codex lists the larger context window. |
Benchmark Deep Dive
Agentic10 benchmarks
| Benchmark | GPT-5.1-Codex | Muse Spark | Result |
|---|---|---|---|
| τ²-bench resultsSource | 83% | 91.5% | Muse Spark leads |
| Gert LabsSource | 49.68% | — | Not comparable |
| JobBenchSource | 26.2% | — | Not comparable |
| Terminal-Bench 2.0Source | — | 59% | Not comparable |
| DeepSearchQASource | — | 74.8% | Not comparable |
| CyberGymSource | — | 43.5% | Not comparable |
| Claw-EvalSource | — | 63.8% | Not comparable |
| AA Agentic IndexSource | — | 28.7% | Not comparable |
| GDPval-AASource | — | 32.2% | Not comparable |
| GDPval-AASource | — | 1144 | Not comparable |
Coding6 benchmarks
| Benchmark | GPT-5.1-Codex | Muse Spark | Result |
|---|---|---|---|
| Vibe Code BenchSource | 13.12% | 19.67% | Muse Spark leads |
| AA-SciCodeSource | 40.2% | 51.5% | Muse Spark leads |
| SWE-bench VerifiedSource | — | 77.4% | Not comparable |
| SWE-bench ProSource | — | 52.4% | Not comparable |
| LiveCodeBench ProSource | — | 80.0% | Not comparable |
| AA Coding IndexSource | — | 58.6% | Not comparable |
Reasoning3 benchmarks
Knowledge11 benchmarks
| Benchmark | GPT-5.1-Codex | Muse Spark | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 34.7% | 43.1% | Muse Spark leads |
| AA-GPQA DiamondSource | 86.0% | 88.4% | Muse Spark leads |
| AA-HLESource | 23.4% | 39.9% | Muse Spark leads |
| AA-Omniscience IndexSource | -6.0% | 4.1% | Muse Spark leads |
| AA-Omniscience AccuracySource | 39.2% | 44.6% | Muse Spark leads |
| AA-Omniscience Hallucination RateSource | 74.4% | 73.2% | Muse Spark leads |
| GPQA-DSource | — | 89.5% | Not comparable |
| HLESource | — | 50.4% | Not comparable |
| HLE w/o toolsSource | — | 42.8% | Not comparable |
| HealthBench HardSource | — | 42.8% | Not comparable |
| MedXpertQA (Text)Source | — | 52.6% | Not comparable |
Math2 benchmarks
Multimodal9 benchmarks
| Benchmark | GPT-5.1-Codex | Muse Spark | Result |
|---|---|---|---|
| AA-MMMU-ProSource | 72.5% | 80.5% | Muse Spark leads |
| Design Arena WebsiteSource | 1191 | — | Not comparable |
| CharXivSource | — | 86.4% | Not comparable |
| MMMU-ProSource | — | 80.4% | Not comparable |
| ERQASource | — | 64.7% | Not comparable |
| SimpleVQASource | — | 71.3% | Not comparable |
| ScreenSpot ProSource | — | 84.1% | Not comparable |
| ZeroBenchSource | — | 33.0% | Not comparable |
| MedXpertQA (MM)Source | — | 78.4% | Not comparable |
Inst. Following1 benchmarks
| Benchmark | GPT-5.1-Codex | Muse Spark | Result |
|---|---|---|---|
| AA-IFBenchSource | 70.0% | 75.9% | Muse Spark leads |
Frequently Asked Questions (2)
Can I compare GPT-5.1-Codex and Muse Spark on BenchLM yet?
Not fully yet. BenchLM is tracking both models, but the sourced benchmark breakdown for this comparison is still coming soon.
Why does this comparison show “coming soon”?
BenchLM only shows category winners and benchmark-level calls when we have sourced results that can be compared fairly. For these models, the public benchmark coverage is not complete enough yet.
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