Agentic
Like-for-like- Gemini 3.6 Flash
- 50.7
- Supported · #60/151
- Gemma 4 31B
- 27.6
- Supported · #140/151
- Basis
- BenchAlign lane · 2 vs 1 public rows
- Reading
- Gemini 3.6 Flash leads · intervals overlap
Gemini 3.6 Flash vs Gemma 4 31B
Updated September 4, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.
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.
Coding work
Code generation, repair, and software-engineering tasks
Gemini 3.6 Flash
Gemini 3.6 Flash leads on the public coding lane, 58.9 to 43.5, with Supported evidence for both models, although the 90% intervals overlap.
Confidence: limited
Agentic work
Tool use, computer use, and multi-step task completion
Gemini 3.6 Flash
Gemini 3.6 Flash leads on the public agentic lane, 50.7 to 27.6, with Supported evidence for both models, although the 90% intervals overlap.
Confidence: limited
Long documents
Prompts that approach the documented context limit
Gemini 3.6 Flash
Gemini 3.6 Flash has the larger documented context window.
Confidence: documented
Show secondary and unsupported calls
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.
8 Gemini 3.6 Flash only
8 Gemma 4 31B only
- Shared results
- 0
- Gemini 3.6 Flash only
- 8
- Gemma 4 31B only
- 8
- 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
- Gemma 4 31B
- 43.5
- Supported · #124/183
- Basis
- BenchAlign lane · 4 vs 2 public rows
- Reading
- Gemini 3.6 Flash leads · intervals overlap
Knowledge
Like-for-like- Gemini 3.6 Flash
- 68.6
- Supported · #18/181
- Gemma 4 31B
- 47.8
- Supported · #104/181
- Basis
- BenchAlign lane · 2 vs 4 public rows
- Reading
- Gemini 3.6 Flash leads · intervals overlap
Reasoning
Not comparable- Gemini 3.6 Flash
- 77.8
- Unranked · 2 rankable rows
- Gemma 4 31B
- 70.1
- Unranked · 2 rankable rows
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Math
Not comparable- Gemini 3.6 Flash
- Not ranked
- Gemma 4 31B
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Multilingual
Not comparable- Gemini 3.6 Flash
- Not ranked
- Gemma 4 31B
- 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
- Gemma 4 31B
- 57.8
- #30/48
- Basis
- Provisional lane · 0 vs 1 weighted rows
- Reading
- Not comparable
Instruction following
Not comparable- Gemini 3.6 Flash
- Not ranked
- Gemma 4 31B
- 92.6
- #12/120
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
| Category | Gemini 3.6 Flash | Gemma 4 31B | Basis | Reading |
|---|---|---|---|---|
| Agentic | 50.7Supported · #60/151 | 27.6Supported · #140/151 | Like-for-likeBenchAlign lane · 2 vs 1 public rows | Gemini 3.6 Flash leads · intervals overlap |
| Coding | 58.9Supported · #30/183 | 43.5Supported · #124/183 | Like-for-likeBenchAlign lane · 4 vs 2 public rows | Gemini 3.6 Flash leads · intervals overlap |
| Knowledge | 68.6Supported · #18/181 | 47.8Supported · #104/181 | Like-for-likeBenchAlign lane · 2 vs 4 public rows | Gemini 3.6 Flash leads · intervals overlap |
| Reasoning | 77.8Unranked · 2 rankable rows | 70.1Unranked · 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 | 82.3Unranked · 1 rankable row | 57.8#30/48 | Not comparableProvisional lane · 0 vs 1 weighted rows | Not comparable |
| Instruction following | Not ranked | 92.6#12/120 | 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 3.6 Flash
- $0.00525
- Fits in one request
- Gemma 4 31B
- Self-hosted; infrastructure cost varies
- Fits in one request
Gemma 4 31B 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
- Gemma 4 31B
- Self-hosted; infrastructure cost varies
- Fits in one request
Gemma 4 31B 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
- Gemma 4 31B
- Self-hosted; infrastructure cost varies
- Fits in one request
- Cached-input rate unavailable
Gemma 4 31B 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 FlashGemma 4 31B
Context window
Maximum documented context; output-token limits may be lower.
Gemini 3.6 Flash
Gemma 4 31B
API model ID
Gemini 3.6 Flash
gemini-3.6-flash
Google Gemini 3.6 Flash model documentationGemma 4 31B
gemma-4-31b-it
Google Gemma Gemini API guideCached-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 pricingGemma 4 31B
No comparable hosted API rate
Documented inputs
Gemini 3.6 Flash
text, image, video, audio, pdf
Google Gemini 3.6 Flash model documentationGemma 4 31B
text, image
Google Gemma 4 model documentationDocumented outputs
Gemini 3.6 Flash
Gemma 4 31B
Provider availability
Gemini 3.6 Flash
Generally Available · Gemini API, Google AI Studio
Google latest Gemini model guideGemma 4 31B
Generally Available · Gemini API, Google AI Studio, open weights
Google Gemma Gemini API guideReasoning profile
Gemini 3.6 Flash
Reasoning
Gemma 4 31B
Reasoning
Weight access
Gemini 3.6 Flash
Proprietary
Gemma 4 31B
Open Weight
License
Gemini 3.6 Flash
Proprietary
Gemma 4 31B
Open Weight
Release date
Gemini 3.6 Flash
2026-07-21
Gemma 4 31B
2026-04-02
If you already use one of these models
- Deployment change
- Both entries list Google as the provider. Confirm endpoint, model ID, limits, and feature support before switching.
- 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
- Gemini 3.6 Flash has the larger documented window (1M).
Run the same representative tasks against both endpoints before changing production traffic.
Self-host vs API cost
Estimates at 50,000 req/day · 1000 tokens/req average.
Gemini 3.6 Flash
API / mo$6,750
Self-host / moNot listed
Break-even—
Proprietary model — self-hosting not applicable.
Gemma 4 31B
API / mo$0
Self-host / mo$429
Break-even—
Benchmark evidence
The full public result ledger is available for audit without forcing a wide desktop table onto a phone.
Browse raw public benchmark evidence16 rows
Agentic
Coding
deepSwe
Gemini 3.6 Flash49%SourceGemma 4 31B—Not directly comparable
cursorBench32
Gemini 3.6 Flash53.5%SourceGemma 4 31B—Not directly comparable
LiveCodeBench (Vals)
Gemini 3.6 Flash88.1%SourceGemma 4 31B—Not directly comparable
SWE-bench (Vals)
Gemini 3.6 Flash79.6%SourceGemma 4 31B—Not directly comparable
SWE-Rebench
Gemini 3.6 Flash—Gemma 4 31B41.6%SourceNot directly comparable
React Native Evals
Gemini 3.6 Flash—Gemma 4 31B75.2%SourceNot directly comparable
Knowledge
GPQA Diamond (Vals)
Gemini 3.6 Flash93.4%SourceGemma 4 31B—Not directly comparable
MMLU-Pro (Vals)
Gemini 3.6 Flash89.3%SourceGemma 4 31B—Not directly comparable
GPQA
Gemini 3.6 Flash—Gemma 4 31B84.3%SourceNot directly comparable
MMLU-Pro
Gemini 3.6 Flash—Gemma 4 31B85.2%SourceNot directly comparable
HLE
Gemini 3.6 Flash—Gemma 4 31B26.5%SourceNot directly comparable
HLE w/o tools
Gemini 3.6 Flash—Gemma 4 31B19.5%SourceNot directly comparable
Multimodal
MMMU-Pro
Gemini 3.6 Flash—Gemma 4 31B76.9%SourceNot directly comparable
Frequently asked questions
Which is better, Gemini 3.6 Flash or Gemma 4 31B?
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 3.6 Flash or Gemma 4 31B?
Gemini 3.6 Flash leads the public coding lane, 58.9 to 43.5, with Supported evidence for both models, although the 90% intervals overlap.
Which is better for agentic tasks, Gemini 3.6 Flash or Gemma 4 31B?
Gemini 3.6 Flash leads the public agentic tasks lane, 50.7 to 27.6, with Supported evidence for both models, although the 90% intervals overlap.
Which costs less, Gemini 3.6 Flash or Gemma 4 31B?
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 Gemma 4 31B?
Gemini 3.6 Flash has the larger documented context window: 1M, compared with 256K.
Related comparisons
Last updated September 4, 2026
Watch Gemini 3.6 Flash vs Gemma 4 31B
One weekly email when material rank, price, or benchmark evidence changes make this matchup worth revisiting.
Read a sample issueJoin 2,000+ readers.