Coding
Directional only- Gemini 3.5 Flash-Lite
- 43.2
- Supported · #104/154
- Qwen3.8-Omni-Flash
- 53.5
- Estimated · #45/154
- Basis
- BenchAlign lane · 4 vs 5 public rows
- Reading
- Directional only
Gemini 3.5 Flash-Lite vs Qwen3.8-Omni-Flash
Decision reading
At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner.
1 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.
Updated September 18, 2026. We do not rank this pair: at least one has no public score. Public scores include evidence status and uncertainty.
Both of these models will change. Get the price, version and retirement notices for the pair, each with its source. Follow model changes
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.
No workload recommendation clears the current evidence threshold.
Use the matched evidence, workload costs, and sourced specifications below instead of treating a point score as a universal answer.
Show secondary and unsupported calls
Coding work
Code generation, repair, and software-engineering tasks
Not enough matched evidence
Qwen3.8-Omni-Flash is scored on Estimated evidence for coding, so the reading is directional rather than like-for-like.
Confidence: limited
Agentic work
Tool use, computer use, and multi-step task completion
Not enough matched evidence
Qwen3.8-Omni-Flash is not ranked on the public lane for agentic, so no winner is named for agentic.
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.
9 Gemini 3.5 Flash-Lite only
1 Shared
18 Qwen3.8-Omni-Flash only
- Shared results
- 1
- Gemini 3.5 Flash-Lite only
- 9
- Qwen3.8-Omni-Flash only
- 18
- Like-for-like categories
- 0 / 8
2 categories rest 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
Directional only- Gemini 3.5 Flash-Lite
- 52.0
- Supported · #69/184
- Qwen3.8-Omni-Flash
- 54.9
- Estimated · #54/184
- Basis
- BenchAlign lane · 2 vs 3 public rows
- Reading
- Directional only
Agentic
Not comparable- Gemini 3.5 Flash-Lite
- 43.2
- Estimated · #103/154
- Qwen3.8-Omni-Flash
- Not ranked
- Basis
- BenchAlign lane · 3 vs 2 public rows
- Reading
- Not comparable
Reasoning
Not comparable- Gemini 3.5 Flash-Lite
- 60.1
- Unranked · 3 rankable rows
- Qwen3.8-Omni-Flash
- Not ranked
- Basis
- Provisional lane · 1 vs 0 weighted rows
- Reading
- Not comparable
Math
Not comparable- Gemini 3.5 Flash-Lite
- Not ranked
- Qwen3.8-Omni-Flash
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Multilingual
Not comparable- Gemini 3.5 Flash-Lite
- Not ranked
- Qwen3.8-Omni-Flash
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Multimodal
Not comparable- Gemini 3.5 Flash-Lite
- 76.4
- #16/48
- Qwen3.8-Omni-Flash
- 85.1
- Unranked · 7 rankable rows
- Basis
- Provisional lane · 0 vs 1 weighted rows
- Reading
- Not comparable
Instruction following
Not comparable- Gemini 3.5 Flash-Lite
- Not ranked
- Qwen3.8-Omni-Flash
- 87.7
- #29/124
- Basis
- Provisional lane · 0 vs 1 weighted rows
- Reading
- Not comparable
| Category | Gemini 3.5 Flash-Lite | Qwen3.8-Omni-Flash | Basis | Reading |
|---|---|---|---|---|
| Coding | 43.2Supported · #104/154 | 53.5Estimated · #45/154 | Directional onlyBenchAlign lane · 4 vs 5 public rows | Directional only |
| Knowledge | 52.0Supported · #69/184 | 54.9Estimated · #54/184 | Directional onlyBenchAlign lane · 2 vs 3 public rows | Directional only |
| Agentic | 43.2Estimated · #103/154 | Not ranked | Not comparableBenchAlign lane · 3 vs 2 public rows | Not comparable |
| Reasoning | 60.1Unranked · 3 rankable rows | Not ranked | 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 | 76.4#16/48 | 85.1Unranked · 7 rankable rows | Not comparableProvisional lane · 0 vs 1 weighted rows | Not comparable |
| Instruction following | Not ranked | 87.7#29/124 | Not comparableProvisional lane · 0 vs 1 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.
SWE-bench Pro
Coding
Gemini 3.5 Flash-Lite: 54.2%Qwen3.8-Omni-Flash: 63.3%Normalized gap 9.1Gemini 3.5 Flash-Lite source Qwen3.8-Omni-Flash 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
- Qwen3.8-Omni-Flash
- API rate not published
- Fits in one request
Qwen3.8-Omni-Flash 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
- Qwen3.8-Omni-Flash
- API rate not published
- Fits in one request
Qwen3.8-Omni-Flash 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
- Qwen3.8-Omni-Flash
- API rate not published
- Fits in one request
- Cached-input rate unavailable
Qwen3.8-Omni-Flash 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-LiteQwen3.8-Omni-Flash
Context window
Maximum documented context; output-token limits may be lower.
Gemini 3.5 Flash-Lite
Qwen3.8-Omni-Flash
API model ID
Gemini 3.5 Flash-Lite
gemini-3.5-flash-lite
Google Gemini 3.5 Flash-Lite model documentationQwen3.8-Omni-Flash
qwen3.8-omni-flash
Alibaba Cloud Model Studio pricingCached-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 pricingQwen3.8-Omni-Flash
No comparable hosted API rate
Alibaba Cloud Model Studio pricingDocumented inputs
Gemini 3.5 Flash-Lite
text, image, video, audio, pdf
Google Gemini 3.5 Flash-Lite model documentationQwen3.8-Omni-Flash
Not sourced
Documented outputs
Gemini 3.5 Flash-Lite
Qwen3.8-Omni-Flash
Not sourced
Provider availability
Gemini 3.5 Flash-Lite
Generally Available · Gemini API, Google AI Studio
Google latest Gemini model guideQwen3.8-Omni-Flash
Not sourced
Reasoning profile
Gemini 3.5 Flash-Lite
Reasoning
Qwen3.8-Omni-Flash
Reasoning
Weight access
Gemini 3.5 Flash-Lite
Proprietary
Qwen3.8-Omni-Flash
Proprietary
License
Gemini 3.5 Flash-Lite
Proprietary
Qwen3.8-Omni-Flash
Proprietary
Release date
Gemini 3.5 Flash-Lite
2026-07-21
Qwen3.8-Omni-Flash
2026-09-18
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
- At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner.
- 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
Terminal-Bench 2.0
Gemini 3.5 Flash-Lite54%SourceQwen3.8-Omni-Flash—Not directly comparable
OSWorld-Verified
Gemini 3.5 Flash-Lite74%SourceQwen3.8-Omni-Flash—Not directly comparable
Terminal-Bench 2.1 (Vals)
Gemini 3.5 Flash-Lite50.2%SourceQwen3.8-Omni-Flash—Not directly comparable
CoWorkBench
Gemini 3.5 Flash-Lite—Qwen3.8-Omni-Flash75.3%SourceNot directly comparable
AndroidWorld
Gemini 3.5 Flash-Lite—Qwen3.8-Omni-Flash87.1%SourceNot directly comparable
Coding
Terminal-Bench 2.0
Gemini 3.5 Flash-Lite54.0%SourceQwen3.8-Omni-Flash—Not directly comparable
SWE-bench Pro
Gemini 3.5 Flash-Lite54.2%SourceQwen3.8-Omni-Flash63.3%SourceQwen3.8-Omni-Flash leads this result
LiveCodeBench (Vals)
Gemini 3.5 Flash-Lite79.0%SourceQwen3.8-Omni-Flash—Not directly comparable
SWE-bench (Vals)
Gemini 3.5 Flash-Lite75.0%SourceQwen3.8-Omni-Flash—Not directly comparable
SWE Multilingual
Gemini 3.5 Flash-Lite—Qwen3.8-Omni-Flash80.5%SourceNot directly comparable
NL2Repo
Gemini 3.5 Flash-Lite—Qwen3.8-Omni-Flash48.9%SourceNot directly comparable
DeepSWE
Gemini 3.5 Flash-Lite—Qwen3.8-Omni-Flash57.8%SourceNot directly comparable
LiveCodeBench v6
Gemini 3.5 Flash-Lite—Qwen3.8-Omni-Flash92.6%SourceNot directly comparable
Reasoning
MRCRv2
Gemini 3.5 Flash-Lite72.2%SourceQwen3.8-Omni-Flash—Not directly comparable
Knowledge
GPQA Diamond (Vals)
Gemini 3.5 Flash-Lite83.8%SourceQwen3.8-Omni-Flash—Not directly comparable
MMLU-Pro (Vals)
Gemini 3.5 Flash-Lite85.8%SourceQwen3.8-Omni-Flash—Not directly comparable
GPQA
Gemini 3.5 Flash-Lite—Qwen3.8-Omni-Flash91%SourceNot directly comparable
GPQA-D
Gemini 3.5 Flash-Lite—Qwen3.8-Omni-Flash91.0%SourceNot directly comparable
HLE
Gemini 3.5 Flash-Lite—Qwen3.8-Omni-Flash36.5%SourceNot directly comparable
Multimodal
Vision2Web
Gemini 3.5 Flash-Lite—Qwen3.8-Omni-Flash62.9%SourceNot directly comparable
ERQA
Gemini 3.5 Flash-Lite—Qwen3.8-Omni-Flash71.0%SourceNot directly comparable
LVBench
Gemini 3.5 Flash-Lite—Qwen3.8-Omni-Flash76.9%SourceNot directly comparable
RealWorldQA
Gemini 3.5 Flash-Lite—Qwen3.8-Omni-Flash87.7%SourceNot directly comparable
MathVision
Gemini 3.5 Flash-Lite—Qwen3.8-Omni-Flash91.8%SourceNot directly comparable
MathVision w/ Python
Gemini 3.5 Flash-Lite—Qwen3.8-Omni-Flash96.2%SourceNot directly comparable
CharXiv w/o tools
Gemini 3.5 Flash-Lite—Qwen3.8-Omni-Flash83.5%SourceNot directly comparable
CharXiv
Gemini 3.5 Flash-Lite—Qwen3.8-Omni-Flash91.4%SourceNot directly comparable
Instruction following
IFBench
Gemini 3.5 Flash-Lite—Qwen3.8-Omni-Flash81.5%SourceNot directly comparable
Questions
Which is better, Gemini 3.5 Flash-Lite or Qwen3.8-Omni-Flash?
At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner. The page therefore keeps the decision tied to the specific documented workload.
Which is better for coding, Gemini 3.5 Flash-Lite or Qwen3.8-Omni-Flash?
Qwen3.8-Omni-Flash scores higher for coding on the public lane, 53.5 to 43.2. Qwen3.8-Omni-Flash is scored on Estimated evidence for coding, so the reading is directional rather than like-for-like. BenchLM does not name a winner for coding from a directional reading; read the shared benchmark rows directly and test the models on the same task set.
Which is better for agentic tasks, Gemini 3.5 Flash-Lite or Qwen3.8-Omni-Flash?
Qwen3.8-Omni-Flash is not ranked on the public lane for agentic tasks, so no winner is named for agentic tasks.
Which costs less, Gemini 3.5 Flash-Lite or Qwen3.8-Omni-Flash?
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 Qwen3.8-Omni-Flash?
Both models list the same context window, 1M.
Related comparisons
Last updated September 18, 2026
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