Coding
Like-for-like- Gemini 3.5 Flash-Lite
- 43.6
- Supported · #121/183
- 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
Gemini 3.5 Flash-Lite 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 60.5, but the 90% score intervals overlap. Treat that as a lead, not a settled winner.
9 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 43.6, with Supported evidence for both models, although the 90% intervals overlap.
Confidence: limited
Show secondary and unsupported calls
Agentic work
Tool use, computer use, and multi-step task completion
Not enough matched evidence
Gemini 3.5 Flash-Lite is scored on Estimated evidence for agentic, so the reading is 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.
1 Gemini 3.5 Flash-Lite only
9 Shared
17 Muse Spark 1.1 only
- Shared results
- 9
- Gemini 3.5 Flash-Lite only
- 1
- Muse Spark 1.1 only
- 17
- Like-for-like categories
- 2 / 8
1 category rests on Estimated evidence or different evidence sets. Those rows remain visible for coverage context but do not name a winner.
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.
Knowledge
Like-for-like- Gemini 3.5 Flash-Lite
- 53.0
- Supported · #71/181
- 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
Agentic
Directional only- Gemini 3.5 Flash-Lite
- 43.4
- Estimated · #104/151
- Muse Spark 1.1
- 62.7
- Supported · #18/151
- Basis
- BenchAlign lane · 3 vs 14 public rows
- Reading
- Directional only
Reasoning
Not comparable- Gemini 3.5 Flash-Lite
- 60.8
- Unranked · 3 rankable rows
- Muse Spark 1.1
- 78.5
- #4/22
- Basis
- Provisional lane · 1 vs 0 weighted rows
- Reading
- Not comparable
Math
Not comparable- Gemini 3.5 Flash-Lite
- Not ranked
- Muse Spark 1.1
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Multilingual
Not comparable- Gemini 3.5 Flash-Lite
- Not ranked
- Muse Spark 1.1
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Multimodal
Not comparable- Gemini 3.5 Flash-Lite
- 76.1
- #16/48
- 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 3.5 Flash-Lite
- Not ranked
- Muse Spark 1.1
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
| Category | Gemini 3.5 Flash-Lite | Muse Spark 1.1 | Basis | Reading |
|---|---|---|---|---|
| Coding | 43.6Supported · #121/183 | 59.9Supported · #25/183 | Like-for-likeBenchAlign lane · 4 vs 4 public rows | Muse Spark 1.1 leads · intervals overlap |
| Knowledge | 53.0Supported · #71/181 | 71.5Supported · #11/181 | Like-for-likeBenchAlign lane · 2 vs 5 public rows | Muse Spark 1.1 leads · intervals overlap |
| Agentic | 43.4Estimated · #104/151 | 62.7Supported · #18/151 | Directional onlyBenchAlign lane · 3 vs 14 public rows | Directional only |
| Reasoning | 60.8Unranked · 3 rankable rows | 78.5#4/22 | Not comparableProvisional lane · 1 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 | 76.1#16/48 | 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.
Terminal-Bench 2.0
Agentic
Gemini 3.5 Flash-Lite: 54%Muse Spark 1.1: 80%Normalized gap 26.0Gemini 3.5 Flash-Lite source Muse Spark 1.1 sourceSWE-bench Pro
Coding
Gemini 3.5 Flash-Lite: 54.2%Muse Spark 1.1: 61.5%Normalized gap 7.3Gemini 3.5 Flash-Lite source Muse Spark 1.1 sourceLiveCodeBench (Vals)
Coding
Gemini 3.5 Flash-Lite: 79.0%Muse Spark 1.1: 85.9%Normalized gap 6.9Gemini 3.5 Flash-Lite source Muse Spark 1.1 sourceOSWorld-Verified
Agentic
Gemini 3.5 Flash-Lite: 74%Muse Spark 1.1: 80.8%Normalized gap 6.8Gemini 3.5 Flash-Lite source Muse Spark 1.1 sourceMMLU-Pro (Vals)
Knowledge
Gemini 3.5 Flash-Lite: 85.8%Muse Spark 1.1: 88.7%Normalized gap 2.9Gemini 3.5 Flash-Lite 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 3.5 Flash-Lite
- $0.00155
- 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 3.5 Flash-Lite
- $0.0225
- 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 3.5 Flash-Lite
- $0.037
- 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 3.5 Flash-LiteMuse Spark 1.1
Context window
Maximum documented context; output-token limits may be lower.
Gemini 3.5 Flash-Lite
Muse Spark 1.1
1M
API model ID
Gemini 3.5 Flash-Lite
gemini-3.5-flash-lite
Google Gemini 3.5 Flash-Lite 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 3.5 Flash-Lite
$0.03 per 1M cached input tokens
Google Gemini API pricingMuse Spark 1.1
No comparable hosted API rate
Documented inputs
Gemini 3.5 Flash-Lite
text, image, video, audio, pdf
Google Gemini 3.5 Flash-Lite model documentationMuse Spark 1.1
Not sourced
Documented outputs
Gemini 3.5 Flash-Lite
Muse Spark 1.1
Not sourced
Provider availability
Gemini 3.5 Flash-Lite
Generally Available · Gemini API, Google AI Studio
Google latest Gemini model guideMuse Spark 1.1
Not sourced
Reasoning profile
Gemini 3.5 Flash-Lite
Reasoning
Muse Spark 1.1
Reasoning
Weight access
Gemini 3.5 Flash-Lite
Proprietary
Muse Spark 1.1
Proprietary
License
Gemini 3.5 Flash-Lite
Proprietary
Muse Spark 1.1
Proprietary
Release date
Gemini 3.5 Flash-Lite
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 60.5, 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 evidence27 rows
Agentic
Terminal-Bench 2.0
Gemini 3.5 Flash-Lite54%SourceMuse Spark 1.180%SourceMuse Spark 1.1 leads this result
OSWorld-Verified
Gemini 3.5 Flash-Lite74%SourceMuse Spark 1.180.8%SourceMuse Spark 1.1 leads this result
Terminal-Bench 2.1 (Vals)
Gemini 3.5 Flash-Lite50.2%SourceMuse Spark 1.169.3%SourceMuse Spark 1.1 leads this result
MCP Atlas
Gemini 3.5 Flash-Lite—Muse Spark 1.188.1%SourceNot directly comparable
Toolathlon
Gemini 3.5 Flash-Lite—Muse Spark 1.175.6%SourceNot directly comparable
WebArena-Verified
Gemini 3.5 Flash-Lite—Muse Spark 1.169%SourceNot directly comparable
DeepSearchQA
Gemini 3.5 Flash-Lite—Muse Spark 1.184.9%SourceNot directly comparable
CyberGym
Gemini 3.5 Flash-Lite—Muse Spark 1.159.0%SourceNot directly comparable
Finance Agent v2
Gemini 3.5 Flash-Lite—Muse Spark 1.157.2%SourceNot directly comparable
deepSwe
Gemini 3.5 Flash-Lite—Muse Spark 1.153.3%SourceNot directly comparable
OSWorld 2.0
Gemini 3.5 Flash-Lite—Muse Spark 1.114.2%SourceNot directly comparable
JobBench
Gemini 3.5 Flash-Lite—Muse Spark 1.154.7%SourceNot directly comparable
Cybench
Gemini 3.5 Flash-Lite—Muse Spark 1.192.9%SourceNot directly comparable
ExploitGym
Gemini 3.5 Flash-Lite—Muse Spark 1.10.8%SourceNot directly comparable
Coding
Terminal-Bench 2.0
Gemini 3.5 Flash-Lite54.0%SourceMuse Spark 1.180.0%SourceMuse Spark 1.1 leads this result
SWE-bench Pro
Gemini 3.5 Flash-Lite54.2%SourceMuse Spark 1.161.5%SourceMuse Spark 1.1 leads this result
LiveCodeBench (Vals)
Gemini 3.5 Flash-Lite79.0%SourceMuse Spark 1.185.9%SourceMuse Spark 1.1 leads this result
SWE-bench (Vals)
Gemini 3.5 Flash-Lite75.0%SourceMuse Spark 1.182.0%SourceMuse Spark 1.1 leads this result
Reasoning
Knowledge
GPQA Diamond (Vals)
Gemini 3.5 Flash-Lite83.8%SourceMuse Spark 1.191.2%SourceMuse Spark 1.1 leads this result
MMLU-Pro (Vals)
Gemini 3.5 Flash-Lite85.8%SourceMuse Spark 1.188.7%SourceMuse Spark 1.1 leads this result
HLE
Gemini 3.5 Flash-Lite—Muse Spark 1.162.1%SourceNot directly comparable
HLE w/o tools
Gemini 3.5 Flash-Lite—Muse Spark 1.152.2%SourceNot directly comparable
HealthBench Professional
Gemini 3.5 Flash-Lite—Muse Spark 1.159.3%SourceNot directly comparable
Multimodal
Frequently asked questions
Which is better, Gemini 3.5 Flash-Lite or Muse Spark 1.1?
Muse Spark 1.1 has the higher public score estimate, 71.78 versus 60.5, 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 3.5 Flash-Lite or Muse Spark 1.1?
Muse Spark 1.1 leads the public coding lane, 59.9 to 43.6, with Supported evidence for both models, although the 90% intervals overlap.
Which is better for agentic tasks, Gemini 3.5 Flash-Lite or Muse Spark 1.1?
Muse Spark 1.1 scores higher for agentic tasks on the public lane, 62.7 to 43.4. Gemini 3.5 Flash-Lite is scored on Estimated evidence for agentic tasks, so the reading is directional rather than like-for-like. BenchLM does not name a winner for agentic tasks from a directional reading; read the shared benchmark rows directly and test the models on the same task set.
Which costs less, Gemini 3.5 Flash-Lite 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 3.5 Flash-Lite or Muse Spark 1.1?
Both models list the same context window, 1M.
Related comparisons
Last updated September 4, 2026
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