Knowledge
Directional only- Gemini 3.7 Flash
- 69.7
- Supported · #13/183
- Qwen3-Omni-30B-A3B-Instruct
- 38.7
- Estimated · #142/183
- Basis
- BenchAlign lane · 6 vs 0 public rows
- Reading
- Directional only
Gemini 3.7 Flash vs Qwen3-Omni-30B-A3B-Instruct
Updated September 10, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.
Alibaba
38.33/100
Estimated · Public rank #200
90% interval 26.8–49.8
Decision reading
The public evidence has no benchmark result shared by both models, so it does not support a quality verdict. Use the documented cost, context, and runtime rows instead.
0 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.
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-Omni-30B-A3B-Instruct is not ranked on the public lane for coding, so no winner is named for coding.
Confidence: limited
Agentic work
Tool use, computer use, and multi-step task completion
Not enough matched evidence
Qwen3-Omni-30B-A3B-Instruct 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
Not enough matched evidence
A complete context comparison is not sourced.
Confidence: limited
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.
22 Gemini 3.7 Flash only
- Shared results
- 0
- Gemini 3.7 Flash only
- 22
- Qwen3-Omni-30B-A3B-Instruct only
- 0
- Like-for-like categories
- 0 / 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.
Agentic
Not comparable- Gemini 3.7 Flash
- 64.0
- Supported · #12/152
- Qwen3-Omni-30B-A3B-Instruct
- Not ranked
- Basis
- BenchAlign lane · 6 vs 0 public rows
- Reading
- Not comparable
Coding
Not comparable- Gemini 3.7 Flash
- 62.7
- Supported · #15/151
- Qwen3-Omni-30B-A3B-Instruct
- Not ranked
- Basis
- BenchAlign lane · 6 vs 0 public rows
- Reading
- Not comparable
Reasoning
Not comparable- Gemini 3.7 Flash
- 77.2
- Unranked · 3 rankable rows
- Qwen3-Omni-30B-A3B-Instruct
- 21.0
- Unranked · 2 rankable rows
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Math
Not comparable- Gemini 3.7 Flash
- Not ranked
- Qwen3-Omni-30B-A3B-Instruct
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Multilingual
Not comparable- Gemini 3.7 Flash
- Not ranked
- Qwen3-Omni-30B-A3B-Instruct
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Multimodal
Not comparable- Gemini 3.7 Flash
- 82.7
- #9/48
- Qwen3-Omni-30B-A3B-Instruct
- 41.8
- Unranked · 1 rankable row
- Basis
- Provisional lane · 1 vs 0 weighted rows
- Reading
- Not comparable
Instruction following
Not comparable- Gemini 3.7 Flash
- Not ranked
- Qwen3-Omni-30B-A3B-Instruct
- 35.2
- #112/123
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
| Category | Gemini 3.7 Flash | Qwen3-Omni-30B-A3B-Instruct | Basis | Reading |
|---|---|---|---|---|
| Knowledge | 69.7Supported · #13/183 | 38.7Estimated · #142/183 | Directional onlyBenchAlign lane · 6 vs 0 public rows | Directional only |
| Agentic | 64.0Supported · #12/152 | Not ranked | Not comparableBenchAlign lane · 6 vs 0 public rows | Not comparable |
| Coding | 62.7Supported · #15/151 | Not ranked | Not comparableBenchAlign lane · 6 vs 0 public rows | Not comparable |
| Reasoning | 77.2Unranked · 3 rankable rows | 21.0Unranked · 2 rankable rows | 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 | 82.7#9/48 | 41.8Unranked · 1 rankable row | Not comparableProvisional lane · 1 vs 0 weighted rows | Not comparable |
| Instruction following | Not ranked | 35.2#112/123 | 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.
A shared-evidence shape is not available.
BenchLM does not draw a radar or infer missing axes when the matched evidence is too sparse.
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 3.7 Flash
- $0.00262
- Fits in one request
- Qwen3-Omni-30B-A3B-Instruct
- API rate not published
- Fit state unavailable
Qwen3-Omni-30B-A3B-Instruct has no comparable published API token rate.
Repository review
50K fresh input + 3K output tokens
- Gemini 3.7 Flash
- $0.04875
- Fits in one request
- Qwen3-Omni-30B-A3B-Instruct
- API rate not published
- Fit state unavailable
Qwen3-Omni-30B-A3B-Instruct has no comparable published API token rate.
Cache-heavy agent loop
200K cached + 20K fresh input + 10K output tokens
- Gemini 3.7 Flash
- $0.0675
- Fits in one request
- Qwen3-Omni-30B-A3B-Instruct
- API rate not published
- Fit state unavailable
- Cached-input rate unavailable
Qwen3-Omni-30B-A3B-Instruct 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 3.7 FlashQwen3-Omni-30B-A3B-Instruct
Context window
Maximum documented context; output-token limits may be lower.
Gemini 3.7 Flash
Qwen3-Omni-30B-A3B-Instruct
N/A
API model ID
Gemini 3.7 Flash
gemini-3.7-flash
Google Gemini 3.7 Flash API documentationQwen3-Omni-30B-A3B-Instruct
Not sourced
Cached-input rate
A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.
Gemini 3.7 Flash
$0.075 per 1M cached input tokens
Google Gemini API pricingQwen3-Omni-30B-A3B-Instruct
No comparable hosted API rate
Alibaba model documentationDocumented inputs
Gemini 3.7 Flash
text, image, video, audio, pdf
Google Gemini 3.7 Flash API documentationQwen3-Omni-30B-A3B-Instruct
Not sourced
Documented outputs
Gemini 3.7 Flash
Qwen3-Omni-30B-A3B-Instruct
Not sourced
Provider availability
Gemini 3.7 Flash
Generally Available · Gemini API, Google AI Studio, Gemini App - Spark, Gemini Enterprise App, Gemini Enterprise Agent Platform, Google Antigravity
Google DeepMind Gemini 3.7 Flash model cardQwen3-Omni-30B-A3B-Instruct
Not sourced
Reasoning profile
Gemini 3.7 Flash
Reasoning
Qwen3-Omni-30B-A3B-Instruct
Non-Reasoning
Weight access
Gemini 3.7 Flash
Proprietary
Qwen3-Omni-30B-A3B-Instruct
Open Weight
License
Gemini 3.7 Flash
Proprietary
Qwen3-Omni-30B-A3B-Instruct
Open Weight
Release date
Gemini 3.7 Flash
2026-08-13
Qwen3-Omni-30B-A3B-Instruct
2025-09-22
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
- The public evidence has no benchmark result shared by both models, so it does not support a quality verdict.
- Workload cost
- A complete comparable API-rate estimate is not available for both models.
- Context tradeoff
- A complete documented context comparison is not available.
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 evidence22 rows
Agentic
Terminal-Bench 2.1
Gemini 3.7 Flash85.8%SourceQwen3-Omni-30B-A3B-Instruct—Not directly comparable
Terminal-Bench 3.0
Gemini 3.7 Flash14.9%SourceQwen3-Omni-30B-A3B-Instruct—Not directly comparable
AutomationBench
Gemini 3.7 Flash30.4%SourceQwen3-Omni-30B-A3B-Instruct—Not directly comparable
OSWorld 2.0
Gemini 3.7 Flash47.9%SourceQwen3-Omni-30B-A3B-Instruct—Not directly comparable
Agents' Last Exam
Gemini 3.7 Flash26.3%SourceQwen3-Omni-30B-A3B-Instruct—Not directly comparable
Terminal-Bench 2.1 (Vals)
Gemini 3.7 Flash77.5%SourceQwen3-Omni-30B-A3B-Instruct—Not directly comparable
Coding
FrontierCode 1.1 Main
Gemini 3.7 Flash43.6%SourceQwen3-Omni-30B-A3B-Instruct—Not directly comparable
DeepSWE
Gemini 3.7 Flash65.3%SourceQwen3-Omni-30B-A3B-Instruct—Not directly comparable
Terminal-Bench 2.1
Gemini 3.7 Flash85.8%SourceQwen3-Omni-30B-A3B-Instruct—Not directly comparable
FrontierSWE v2
Gemini 3.7 Flash20.3%SourceQwen3-Omni-30B-A3B-Instruct—Not directly comparable
LiveCodeBench (Vals)
Gemini 3.7 Flash88.7%SourceQwen3-Omni-30B-A3B-Instruct—Not directly comparable
SWE-bench (Vals)
Gemini 3.7 Flash80.8%SourceQwen3-Omni-30B-A3B-Instruct—Not directly comparable
Reasoning
MRCR v2 64K-128K
Gemini 3.7 Flash97%SourceQwen3-Omni-30B-A3B-Instruct—Not directly comparable
Knowledge
HLE-Verified
Gemini 3.7 Flash53.6%SourceQwen3-Omni-30B-A3B-Instruct—Not directly comparable
LABBench2
Gemini 3.7 Flash82.1%SourceQwen3-Omni-30B-A3B-Instruct—Not directly comparable
BioMysteryBench (human-solvable)
Gemini 3.7 Flash87.1%SourceQwen3-Omni-30B-A3B-Instruct—Not directly comparable
BioMysteryBench (human-difficult)
Gemini 3.7 Flash43.5%SourceQwen3-Omni-30B-A3B-Instruct—Not directly comparable
GPQA Diamond (Vals)
Gemini 3.7 Flash93.9%SourceQwen3-Omni-30B-A3B-Instruct—Not directly comparable
MMLU-Pro (Vals)
Gemini 3.7 Flash90.1%SourceQwen3-Omni-30B-A3B-Instruct—Not directly comparable
Multimodal
Frequently asked questions
Which is better, Gemini 3.7 Flash or Qwen3-Omni-30B-A3B-Instruct?
The public evidence has no benchmark result shared by both models, so it does not support a quality verdict. The page therefore keeps the decision tied to the specific documented workload.
Which is better for coding, Gemini 3.7 Flash or Qwen3-Omni-30B-A3B-Instruct?
Qwen3-Omni-30B-A3B-Instruct is not ranked on the public lane for coding, so no winner is named for coding.
Which is better for agentic tasks, Gemini 3.7 Flash or Qwen3-Omni-30B-A3B-Instruct?
Qwen3-Omni-30B-A3B-Instruct is not ranked on the public lane for agentic tasks, so no winner is named for agentic tasks.
Which costs less, Gemini 3.7 Flash or Qwen3-Omni-30B-A3B-Instruct?
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 3.7 Flash or Qwen3-Omni-30B-A3B-Instruct?
A complete documented context-window comparison is not available.
Related comparisons
Last updated September 10, 2026
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