Agentic
Like-for-like- Gemini 3.6 Flash
- 50.7
- Supported · #60/151
- Muse Spark 1.1
- 62.7
- Supported · #18/151
- Basis
- BenchAlign lane · 2 vs 14 public rows
- Reading
- Muse Spark 1.1 leads · intervals overlap
Gemini 3.6 Flash vs Muse Spark 1.1
Updated September 4, 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, 71.78 versus 70.11, but the 90% score intervals overlap. Treat that as a lead, not a settled winner.
6 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.
Share or export
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 public coding lane, 59.9 to 58.9, with Supported evidence for both models, although the 90% intervals overlap.
Confidence: limited
Agentic work
Tool use, computer use, and multi-step task completion
Muse Spark 1.1
Muse Spark 1.1 leads on the public agentic lane, 62.7 to 50.7, with Supported evidence for both models, although the 90% intervals overlap.
Confidence: limited
Show secondary and unsupported calls
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.
2 Gemini 3.6 Flash only
6 Shared
20 Muse Spark 1.1 only
- Shared results
- 6
- Gemini 3.6 Flash only
- 2
- Muse Spark 1.1 only
- 20
- Like-for-like categories
- 3 / 8
Category results, on a stated basis
Each row shows the public-lane category score for both models: the BenchAlign lane for agentic, coding, and knowledge, and the weighted public rows elsewhere, with the same rank each model page reports. A row is like-for-like only when both scores rest on Supported evidence or the same weighted set. Directional and not-comparable rows remain visible, but they never receive a winner.
Coding
Like-for-like- Gemini 3.6 Flash
- 58.9
- Supported · #30/183
- Muse Spark 1.1
- 59.9
- Supported · #25/183
- Basis
- BenchAlign lane · 4 vs 4 public rows
- Reading
- Muse Spark 1.1 leads · intervals overlap
Knowledge
Like-for-like- Gemini 3.6 Flash
- 68.6
- Supported · #18/181
- Muse Spark 1.1
- 71.5
- Supported · #11/181
- Basis
- BenchAlign lane · 2 vs 5 public rows
- Reading
- Muse Spark 1.1 leads · intervals overlap
Reasoning
Not comparable- Gemini 3.6 Flash
- 77.8
- Unranked · 2 rankable rows
- Muse Spark 1.1
- 78.5
- #4/22
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Math
Not comparable- Gemini 3.6 Flash
- Not ranked
- Muse Spark 1.1
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Multilingual
Not comparable- Gemini 3.6 Flash
- Not ranked
- Muse Spark 1.1
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Multimodal
Not comparable- Gemini 3.6 Flash
- 82.3
- Unranked · 1 rankable row
- Muse Spark 1.1
- 77.2
- Unranked · 2 rankable rows
- Basis
- Provisional lane · 0 vs 1 weighted rows
- Reading
- Not comparable
Instruction following
Not comparable- Gemini 3.6 Flash
- Not ranked
- Muse Spark 1.1
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
| Category | Gemini 3.6 Flash | Muse Spark 1.1 | Basis | Reading |
|---|---|---|---|---|
| Agentic | 50.7Supported · #60/151 | 62.7Supported · #18/151 | Like-for-likeBenchAlign lane · 2 vs 14 public rows | Muse Spark 1.1 leads · intervals overlap |
| Coding | 58.9Supported · #30/183 | 59.9Supported · #25/183 | Like-for-likeBenchAlign lane · 4 vs 4 public rows | Muse Spark 1.1 leads · intervals overlap |
| Knowledge | 68.6Supported · #18/181 | 71.5Supported · #11/181 | Like-for-likeBenchAlign lane · 2 vs 5 public rows | Muse Spark 1.1 leads · intervals overlap |
| Reasoning | 77.8Unranked · 2 rankable rows | 78.5#4/22 | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Math | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Multilingual | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Multimodal | 82.3Unranked · 1 rankable row | 77.2Unranked · 2 rankable rows | Not comparableProvisional lane · 0 vs 1 weighted rows | Not comparable |
| Instruction following | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
Ranks count the models scored in each category’s lane, so the agentic, coding, and knowledge denominators (BenchAlign) differ from the provisional-lane categories. Unranked scores sit on the lane’s scale but never name a winner. Like-for-like rows within 0.5 points read as a practical tie.
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.
OSWorld-Verified
Agentic
Gemini 3.6 Flash: 83%Muse Spark 1.1: 80.8%Normalized gap 2.2Gemini 3.6 Flash source Muse Spark 1.1 sourceLiveCodeBench (Vals)
Coding
Gemini 3.6 Flash: 88.1%Muse Spark 1.1: 85.9%Normalized gap 2.2Gemini 3.6 Flash source Muse Spark 1.1 sourceMMLU-Pro (Vals)
Knowledge
Gemini 3.6 Flash: 89.3%Muse Spark 1.1: 88.7%Normalized gap 0.6Gemini 3.6 Flash source Muse Spark 1.1 source
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
- Gemini 3.6 Flash
- $0.00525
- 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
- Gemini 3.6 Flash
- $0.0975
- 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
- Gemini 3.6 Flash
- $0.135
- 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.
SpecificationGemini 3.6 FlashMuse Spark 1.1
Context window
Maximum documented context; output-token limits may be lower.
Gemini 3.6 Flash
Muse Spark 1.1
1M
API model ID
Gemini 3.6 Flash
gemini-3.6-flash
Google Gemini 3.6 Flash model documentationMuse 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.
Gemini 3.6 Flash
$0.15 per 1M cached input tokens
Google Gemini API pricingMuse Spark 1.1
No comparable hosted API rate
Documented inputs
Gemini 3.6 Flash
text, image, video, audio, pdf
Google Gemini 3.6 Flash model documentationMuse Spark 1.1
Not sourced
Documented outputs
Gemini 3.6 Flash
Muse Spark 1.1
Not sourced
Provider availability
Gemini 3.6 Flash
Generally Available · Gemini API, Google AI Studio
Google latest Gemini model guideMuse Spark 1.1
Not sourced
Reasoning profile
Gemini 3.6 Flash
Reasoning
Muse Spark 1.1
Reasoning
Weight access
Gemini 3.6 Flash
Proprietary
Muse Spark 1.1
Proprietary
License
Gemini 3.6 Flash
Proprietary
Muse Spark 1.1
Proprietary
Release date
Gemini 3.6 Flash
2026-07-21
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, 71.78 versus 70.11, 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 evidence28 rows
Agentic
OSWorld-Verified
Gemini 3.6 Flash83%SourceMuse Spark 1.180.8%SourceGemini 3.6 Flash leads this result
Terminal-Bench 2.1 (Vals)
Gemini 3.6 Flash73.8%SourceMuse Spark 1.169.3%SourceGemini 3.6 Flash leads this result
Terminal-Bench 2.0
Gemini 3.6 Flash—Muse Spark 1.180%SourceNot directly comparable
MCP Atlas
Gemini 3.6 Flash—Muse Spark 1.188.1%SourceNot directly comparable
Toolathlon
Gemini 3.6 Flash—Muse Spark 1.175.6%SourceNot directly comparable
WebArena-Verified
Gemini 3.6 Flash—Muse Spark 1.169%SourceNot directly comparable
DeepSearchQA
Gemini 3.6 Flash—Muse Spark 1.184.9%SourceNot directly comparable
CyberGym
Gemini 3.6 Flash—Muse Spark 1.159.0%SourceNot directly comparable
Finance Agent v2
Gemini 3.6 Flash—Muse Spark 1.157.2%SourceNot directly comparable
deepSwe
Gemini 3.6 Flash—Muse Spark 1.153.3%SourceNot directly comparable
OSWorld 2.0
Gemini 3.6 Flash—Muse Spark 1.114.2%SourceNot directly comparable
JobBench
Gemini 3.6 Flash—Muse Spark 1.154.7%SourceNot directly comparable
Cybench
Gemini 3.6 Flash—Muse Spark 1.192.9%SourceNot directly comparable
ExploitGym
Gemini 3.6 Flash—Muse Spark 1.10.8%SourceNot directly comparable
Coding
deepSwe
Gemini 3.6 Flash49%SourceMuse Spark 1.1—Not directly comparable
cursorBench32
Gemini 3.6 Flash53.5%SourceMuse Spark 1.1—Not directly comparable
LiveCodeBench (Vals)
Gemini 3.6 Flash88.1%SourceMuse Spark 1.185.9%SourceGemini 3.6 Flash leads this result
SWE-bench (Vals)
Gemini 3.6 Flash79.6%SourceMuse Spark 1.182.0%SourceMuse Spark 1.1 leads this result
Terminal-Bench 2.0
Gemini 3.6 Flash—Muse Spark 1.180.0%SourceNot directly comparable
SWE-bench Pro
Gemini 3.6 Flash—Muse Spark 1.161.5%SourceNot directly comparable
Reasoning
MRCR 1M
Gemini 3.6 Flash—Muse Spark 1.154.1%SourceNot directly comparable
Knowledge
GPQA Diamond (Vals)
Gemini 3.6 Flash93.4%SourceMuse Spark 1.191.2%SourceGemini 3.6 Flash leads this result
MMLU-Pro (Vals)
Gemini 3.6 Flash89.3%SourceMuse Spark 1.188.7%SourceGemini 3.6 Flash leads this result
HLE
Gemini 3.6 Flash—Muse Spark 1.162.1%SourceNot directly comparable
HLE w/o tools
Gemini 3.6 Flash—Muse Spark 1.152.2%SourceNot directly comparable
HealthBench Professional
Gemini 3.6 Flash—Muse Spark 1.159.3%SourceNot directly comparable
Multimodal
Frequently asked questions
Which is better, Gemini 3.6 Flash or Muse Spark 1.1?
Muse Spark 1.1 has the higher public score estimate, 71.78 versus 70.11, but the 90% score intervals overlap. The higher estimate is not a decisive winner because the uncertainty ranges overlap.
Which is better for coding, Gemini 3.6 Flash or Muse Spark 1.1?
Muse Spark 1.1 leads the public coding lane, 59.9 to 58.9, with Supported evidence for both models, although the 90% intervals overlap.
Which is better for agentic tasks, Gemini 3.6 Flash or Muse Spark 1.1?
Muse Spark 1.1 leads the public agentic tasks lane, 62.7 to 50.7, with Supported evidence for both models, although the 90% intervals overlap.
Which costs less, Gemini 3.6 Flash 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, Gemini 3.6 Flash or Muse Spark 1.1?
Both models list the same context window, 1M.
Related comparisons
Last updated September 4, 2026
Watch Gemini 3.6 Flash vs Muse Spark 1.1
One weekly email when material rank, price, or benchmark evidence changes make this matchup worth revisiting.
Read a sample issueJoin 2,000+ readers.