Coding
Like-for-like- GPT-5.5
- 58.6
- Muse Spark 1.1
- 61.5
- Weighted basis
- 1 vs 1 rows
- Reading
- Muse Spark 1.1 leads
GPT-5.5 vs Muse Spark 1.1
Updated August 22, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.
Decision reading
Muse Spark 1.1 has the higher public score estimate, 76.74 versus 73.33, but the 90% score intervals overlap. Treat that as a lead, not a settled winner.
12 results are shared. Category rows based on different benchmark sets are marked directional and do not name a winner.
Which one for your work
Recommendations appear only when a shared evidence basis or an explicit operating constraint supports the call. Secondary and unsupported use cases stay disclosed below the initial list.
Coding work
Code generation, repair, and software-engineering tasks
Muse Spark 1.1
Muse Spark 1.1 leads on the same 1 weighted benchmark row.
Confidence: limited
Show secondary and unsupported calls
Agentic work
Tool use, computer use, and multi-step task completion
Not enough matched evidence
The category averages use different weighted benchmark sets, so they are directional rather than like-for-like.
Confidence: limited
Long documents
Prompts that approach the documented context limit
No clear pick
The documented context windows are equal.
Confidence: documented
Chat turn cost
1K fresh input + 500 output tokens
Not enough matched evidence
A complete comparable API-rate estimate is not available for both models.
Confidence: listed-rates
Cache-heavy agent loop cost
200K cached + 20K fresh input + 10K output tokens
Not enough matched evidence
A complete comparable API-rate estimate is not available for both models.
Confidence: listed-rates
Repository review cost
50K fresh input + 3K output tokens
Not enough matched evidence
A complete comparable API-rate estimate is not available for both models.
Confidence: listed-rates
What is actually comparable
Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.
21 GPT-5.5 only
12 Shared
9 Muse Spark 1.1 only
- Shared results
- 12
- GPT-5.5 only
- 21
- Muse Spark 1.1 only
- 9
- Like-for-like categories
- 1 / 8
2 categories use different evidence sets. Those rows remain visible for coverage context but do not name a winner.
Category results, on a stated basis
Each row states whether both averages use the same weighted benchmark set. Directional and not-comparable rows remain visible, but they never receive a winner in this template.
Agentic
Directional only- GPT-5.5
- 81.6
- Muse Spark 1.1
- 80.4
- Weighted basis
- 3 vs 2 rows
- Reading
- Directional only
Knowledge
Directional only- GPT-5.5
- 57.8
- Muse Spark 1.1
- 62.1
- Weighted basis
- 2 vs 1 rows
- Reading
- Directional only
Reasoning
Not comparable- GPT-5.5
- 85.0
- Muse Spark 1.1
- Not measured
- Weighted basis
- 1 vs 0 rows
- Reading
- Not comparable
Math
Not comparable- GPT-5.5
- 47.6
- Muse Spark 1.1
- Not measured
- Weighted basis
- 2 vs 0 rows
- Reading
- Not comparable
Multilingual
Not comparable- GPT-5.5
- Not measured
- Muse Spark 1.1
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
Multimodal
Not comparable- GPT-5.5
- 70.4
- Muse Spark 1.1
- 88.4
- Weighted basis
- 2 vs 1 rows
- Reading
- Not comparable
Instruction following
Not comparable- GPT-5.5
- Not measured
- Muse Spark 1.1
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
| Category | GPT-5.5 | Muse Spark 1.1 | Weighted basis | Reading |
|---|---|---|---|---|
| Coding | 58.6 | 61.5 | Like-for-like1 vs 1 rows | Muse Spark 1.1 leads |
| Agentic | 81.6 | 80.4 | Directional only3 vs 2 rows | Directional only |
| Knowledge | 57.8 | 62.1 | Directional only2 vs 1 rows | Directional only |
| Reasoning | 85.0 | Not measured | Not comparable1 vs 0 rows | Not comparable |
| Math | 47.6 | Not measured | Not comparable2 vs 0 rows | Not comparable |
| Multilingual | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
| Multimodal | 70.4 | 88.4 | Not comparable2 vs 1 rows | Not comparable |
| Instruction following | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
Shape of the matched evidence
Only shared public evidence is shown. Sparse evidence stays a ruled list rather than being closed into a radar shape.
Too few matched category axes support a radar. The ruled list below shows only shared benchmark results; positions use each benchmark’s normalized display scale when available.
HLE
Knowledge
SWE-bench Pro
Coding
OSWorld-Verified
Agentic
Terminal-Bench 2.0
Agentic
What each workload costs
Three fixed token mixes turn per-token rates into comparable decisions. Each scenario states context fit and whether cached input had to fall back to the published list-input rate.
Chat turn
1K fresh input + 500 output tokens
- GPT-5.5
- $0.02
- Fits in one request
- Muse Spark 1.1
- API rate not published
- Fits in one request
Muse Spark 1.1 has no comparable published API token rate.
Repository review
50K fresh input + 3K output tokens
- GPT-5.5
- $0.34
- Fits in one request
- Muse Spark 1.1
- API rate not published
- Fits in one request
Muse Spark 1.1 has no comparable published API token rate.
Cache-heavy agent loop
200K cached + 20K fresh input + 10K output tokens
- GPT-5.5
- $0.5
- Fits in one request
- Muse Spark 1.1
- API rate not published
- Fits in one request
- Cached-input rate unavailable
Muse Spark 1.1 has no comparable published API token rate.
Specification differences
Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.
SpecificationGPT-5.5Muse Spark 1.1
Context window
Maximum documented context; output-token limits may be lower.
GPT-5.5
Muse Spark 1.1
1M
API model ID
GPT-5.5
gpt-5.5
OpenAI pricingMuse Spark 1.1
Not sourced
Cached-input rate
A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.
GPT-5.5
$0.5 per 1M cached input tokens
OpenAI pricingMuse Spark 1.1
No comparable hosted API rate
Documented inputs
GPT-5.5
Not sourced
Muse Spark 1.1
Not sourced
Documented outputs
GPT-5.5
Not sourced
Muse Spark 1.1
Not sourced
Provider availability
GPT-5.5
Not sourced
Muse Spark 1.1
Not sourced
Reasoning profile
GPT-5.5
Reasoning
Muse Spark 1.1
Reasoning
Weight access
GPT-5.5
Proprietary
Muse Spark 1.1
Proprietary
License
GPT-5.5
Proprietary
Muse Spark 1.1
Proprietary
Release date
GPT-5.5
2026-04-23
Muse Spark 1.1
2026-07-09
If you already use one of these models
- Deployment change
- The models list different providers, so authentication, endpoint behavior, limits, and feature support may change.
- Quality signal
- Muse Spark 1.1 has the higher public score estimate, 76.74 versus 73.33, but the 90% score intervals overlap.
- Workload cost
- A complete comparable API-rate estimate is not available for both models.
- Context tradeoff
- Both models list 1M.
Run the same representative tasks against both endpoints before changing production traffic.
Benchmark evidence
The full public result ledger is available for audit without forcing a wide desktop table onto a phone.
Browse raw public benchmark evidence42 rows
Agentic
Terminal-Bench 2.0
GPT-5.582%SourceMuse Spark 1.180%SourceGPT-5.5 leads this result
CyberGym
GPT-5.581.8%SourceMuse Spark 1.159.0%SourceGPT-5.5 leads this result
BrowseComp
GPT-5.584.4%SourceMuse Spark 1.1—Not directly comparable
OSWorld-Verified
GPT-5.578.7%SourceMuse Spark 1.180.8%SourceMuse Spark 1.1 leads this result
MCP Atlas
GPT-5.575.3%SourceMuse Spark 1.188.1%SourceMuse Spark 1.1 leads this result
Toolathlon
GPT-5.555.6%SourceMuse Spark 1.175.6%SourceMuse Spark 1.1 leads this result
τ²-bench results
GPT-5.598%SourceMuse Spark 1.1—Not directly comparable
Gert Labs
GPT-5.572.93%SourceMuse Spark 1.1—Not directly comparable
ResearchClawBench
GPT-5.517.0%SourceMuse Spark 1.1—Not directly comparable
OSWorld 2.0
GPT-5.513.0%SourceMuse Spark 1.114.2%SourceMuse Spark 1.1 leads this result
JobBench
GPT-5.542.7%SourceMuse Spark 1.154.7%SourceMuse Spark 1.1 leads this result
ExploitGym
GPT-5.513.4%SourceMuse Spark 1.10.8%SourceGPT-5.5 leads this result
WebArena-Verified
GPT-5.5—Muse Spark 1.169%SourceNot directly comparable
DeepSearchQA
GPT-5.5—Muse Spark 1.184.9%SourceNot directly comparable
Finance Agent v2
GPT-5.5—Muse Spark 1.157.2%SourceNot directly comparable
deepSwe
GPT-5.5—Muse Spark 1.153.3%SourceNot directly comparable
Cybench
GPT-5.5—Muse Spark 1.192.9%SourceNot directly comparable
Coding
SWE-bench Pro
GPT-5.558.6%SourceMuse Spark 1.161.5%SourceMuse Spark 1.1 leads this result
Terminal-Bench 2.0
GPT-5.582.0%SourceMuse Spark 1.180.0%SourceGPT-5.5 leads this result
Vibe Code Bench
GPT-5.569.85%SourceMuse Spark 1.1—Not directly comparable
React Native Evals
GPT-5.584.7%SourceMuse Spark 1.1—Not directly comparable
cursorBench31
GPT-5.559.2%SourceMuse Spark 1.1—Not directly comparable
cursorBench32
GPT-5.558.4%SourceMuse Spark 1.1—Not directly comparable
FrontierCode 1.1 Main
GPT-5.543.0%SourceMuse Spark 1.1—Not directly comparable
Reasoning
MRCR v2 64K-128K
GPT-5.583.1%SourceMuse Spark 1.1—Not directly comparable
MRCR v2 128K-256K
GPT-5.587.5%SourceMuse Spark 1.1—Not directly comparable
ARC-AGI-2
GPT-5.585%SourceMuse Spark 1.1—Not directly comparable
ARC-AGI-3
GPT-5.50.4%SourceMuse Spark 1.1—Not directly comparable
MRCR 1M
GPT-5.5—Muse Spark 1.154.1%SourceNot directly comparable
Knowledge
GPQA
GPT-5.593.6%SourceMuse Spark 1.1—Not directly comparable
GPQA-D
GPT-5.593.6%SourceMuse Spark 1.1—Not directly comparable
HLE
GPT-5.552.2%SourceMuse Spark 1.162.1%SourceMuse Spark 1.1 leads this result
HLE w/o tools
GPT-5.541.4%SourceMuse Spark 1.152.2%SourceMuse Spark 1.1 leads this result
HealthBench Professional
GPT-5.5—Muse Spark 1.159.3%SourceNot directly comparable
Math
Multimodal
MMMU-Pro
GPT-5.581.2%SourceMuse Spark 1.1—Not directly comparable
MMMU-Pro w/ Python
GPT-5.583.2%SourceMuse Spark 1.1—Not directly comparable
OfficeQA Pro
GPT-5.554.1%SourceMuse Spark 1.1—Not directly comparable
CharXiv
GPT-5.5—Muse Spark 1.188.4%SourceNot directly comparable
BabyVision
GPT-5.5—Muse Spark 1.176.3%SourceNot directly comparable
Frequently asked questions
Which is better, GPT-5.5 or Muse Spark 1.1?
Muse Spark 1.1 has the higher public score estimate, 76.74 versus 73.33, but the 90% score intervals overlap. The higher estimate is not a decisive winner because the uncertainty ranges overlap.
Which is better for coding, GPT-5.5 or Muse Spark 1.1?
Muse Spark 1.1 leads the like-for-like coding comparison across 1 shared weighted benchmark row.
Which is better for agentic tasks, GPT-5.5 or Muse Spark 1.1?
The current agentic tasks averages use different weighted benchmark sets, so BenchLM does not name a winner from them. Read the shared benchmark rows directly and test the models on the same task set.
Which costs less, GPT-5.5 or Muse Spark 1.1?
Both models do not have comparable published API token rates, so this page does not name a universal price winner.
Which has the larger context window, GPT-5.5 or Muse Spark 1.1?
Both models list the same context window, 1M.
Related comparisons
Last updated August 22, 2026
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