Agentic
Not comparable- Gemini 3.7 Flash
- Not measured
- Gemini 3.8 Flash
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
Gemini 3.7 Flash vs Gemini 3.8 Flash
Updated September 2, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.
Decision reading
Gemini 3.8 Flash has the higher public score estimate, 75.37 versus 75.27, but the 90% score intervals overlap. Treat that as a lead, not a settled winner.
10 results are shared. Category rows based on different benchmark sets are marked directional and do not name a winner.
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
No shared weighted benchmark basis supports a winner.
Confidence: limited
Agentic work
Tool use, computer use, and multi-step task completion
Not enough matched evidence
No shared weighted benchmark basis supports a winner.
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
No clear pick
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
No clear pick
A complete comparable API-rate estimate is not available for both models.
Confidence: listed-rates
Repository review cost
50K fresh input + 3K output tokens
No clear pick
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.
7 Gemini 3.7 Flash only
10 Shared
2 Gemini 3.8 Flash only
- Shared results
- 10
- Gemini 3.7 Flash only
- 7
- Gemini 3.8 Flash only
- 2
- Like-for-like categories
- 0 / 8
Category results, on a stated basis
Each row states whether both averages use the same weighted benchmark set. Directional and not-comparable rows remain visible, but they never receive a winner in this template.
Coding
Not comparable- Gemini 3.7 Flash
- Not measured
- Gemini 3.8 Flash
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
Reasoning
Not comparable- Gemini 3.7 Flash
- Not measured
- Gemini 3.8 Flash
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
Knowledge
Not comparable- Gemini 3.7 Flash
- Not measured
- Gemini 3.8 Flash
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
Math
Not comparable- Gemini 3.7 Flash
- Not measured
- Gemini 3.8 Flash
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
Multilingual
Not comparable- Gemini 3.7 Flash
- Not measured
- Gemini 3.8 Flash
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
Multimodal
Not comparable- Gemini 3.7 Flash
- 88.7
- Gemini 3.8 Flash
- Not measured
- Weighted basis
- 1 vs 0 rows
- Reading
- Not comparable
Instruction following
Not comparable- Gemini 3.7 Flash
- Not measured
- Gemini 3.8 Flash
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
| Category | Gemini 3.7 Flash | Gemini 3.8 Flash | Weighted basis | Reading |
|---|---|---|---|---|
| Agentic | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
| Coding | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
| Reasoning | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
| Knowledge | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
| Math | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
| Multilingual | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
| Multimodal | 88.7 | Not measured | Not comparable1 vs 0 rows | Not comparable |
| Instruction following | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
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
- Gemini 3.8 Flash
- $0.00262
- Fits in one request
Modeled costs are equal
Costs use the listed standard API rates.
Repository review
50K fresh input + 3K output tokens
- Gemini 3.7 Flash
- $0.04875
- Fits in one request
- Gemini 3.8 Flash
- $0.04875
- Fits in one request
Modeled costs are equal
Costs use the listed standard API rates.
Cache-heavy agent loop
200K cached + 20K fresh input + 10K output tokens
- Gemini 3.7 Flash
- $0.0675
- Fits in one request
- Gemini 3.8 Flash
- $0.0675
- Fits in one request
Modeled costs are equal
Costs use the listed standard API rates.
Specification differences
Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.
SpecificationGemini 3.7 FlashGemini 3.8 Flash
Context window
Maximum documented context; output-token limits may be lower.
Gemini 3.7 Flash
Gemini 3.8 Flash
API model ID
Gemini 3.7 Flash
gemini-3.7-flash
Google Gemini 3.7 Flash API documentationGemini 3.8 Flash
gemini-3.8-flash
Google Gemini 3.8 Flash API documentationCached-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 pricingGemini 3.8 Flash
$0.075 per 1M cached input tokens
Google Gemini API pricingDocumented inputs
Gemini 3.7 Flash
text, image, video, audio, pdf
Google Gemini 3.7 Flash API documentationGemini 3.8 Flash
text, image, video, audio, pdf
Google Gemini 3.8 Flash API documentationDocumented outputs
Gemini 3.7 Flash
Gemini 3.8 Flash
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 cardGemini 3.8 Flash
Generally Available · Gemini API, Google AI Studio, Android Studio, Stitch, Gemini app, Gemini Enterprise, Google AI Mode, Google Sheets, Google Antigravity
Google Gemini 3.8 Flash and Gemini 3.8 Flash Cyber launchReasoning profile
Gemini 3.7 Flash
Reasoning
Gemini 3.8 Flash
Reasoning
Weight access
Gemini 3.7 Flash
Proprietary
Gemini 3.8 Flash
Proprietary
License
Gemini 3.7 Flash
Proprietary
Gemini 3.8 Flash
Proprietary
Release date
Gemini 3.7 Flash
2026-08-13
Gemini 3.8 Flash
2026-09-02
If you are considering the documented upgrade path
- Deployment change
- Both entries list Google as the provider. Confirm endpoint, model ID, limits, and feature support before switching.
- Quality signal
- Gemini 3.8 Flash has the higher public score estimate, 75.37 versus 75.27, but the 90% score intervals overlap.
- Workload cost
- Repository review: $0.04875 vs $0.04875. Cache-heavy agent loop: $0.0675 vs $0.0675.
- 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 evidence19 rows
Agentic
Terminal-Bench 2.1
Gemini 3.7 Flash85.8%SourceGemini 3.8 Flash89.4%SourceGemini 3.8 Flash leads this result
Terminal-Bench 3.0
Gemini 3.7 Flash14.9%SourceGemini 3.8 Flash—Not directly comparable
AutomationBench
Gemini 3.7 Flash30.4%SourceGemini 3.8 Flash—Not directly comparable
OSWorld 2.0
Gemini 3.7 Flash47.9%SourceGemini 3.8 Flash59.0%SourceGemini 3.8 Flash leads this result
Agents' Last Exam
Gemini 3.7 Flash26.3%SourceGemini 3.8 Flash—Not directly comparable
Finance Agent v2
Gemini 3.7 Flash—Gemini 3.8 Flash61.4%SourceNot directly comparable
Terminal-Bench 4.0
Gemini 3.7 Flash—Gemini 3.8 Flash19.10%SourceNot directly comparable
Coding
FrontierCode 1.1 Main
Gemini 3.7 Flash43.6%SourceGemini 3.8 Flash—Not directly comparable
deepSwe
Gemini 3.7 Flash65.3%SourceGemini 3.8 Flash73.8%SourceGemini 3.8 Flash leads this result
Terminal-Bench 2.1
Gemini 3.7 Flash85.8%SourceGemini 3.8 Flash89.4%SourceGemini 3.8 Flash leads this result
cursorBench32
Gemini 3.7 Flash61.6%SourceGemini 3.8 Flash—Not directly comparable
Reasoning
MRCR v2 64K-128K
Gemini 3.7 Flash97%SourceGemini 3.8 Flash—Not directly comparable
Knowledge
HLE-Verified
Shared sourceGemini 3.7 Flash53.6%Gemini 3.8 Flash54.9%Gemini 3.8 Flash leads this result
LABBench2
Shared sourceGemini 3.7 Flash82.1%Gemini 3.8 Flash86.2%Gemini 3.8 Flash leads this result
BioMysteryBench (human-solvable)
Gemini 3.7 Flash87.1%SourceGemini 3.8 Flash88.8%SourceGemini 3.8 Flash leads this result
BioMysteryBench (human-difficult)
Gemini 3.7 Flash43.5%SourceGemini 3.8 Flash56.5%SourceGemini 3.8 Flash leads this result
Multimodal
Frequently asked questions
Which is better, Gemini 3.7 Flash or Gemini 3.8 Flash?
Gemini 3.8 Flash has the higher public score estimate, 75.37 versus 75.27, 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 3.7 Flash or Gemini 3.8 Flash?
The published evidence does not provide a shared weighted coding basis for both models, so BenchLM does not name a coding winner.
Which is better for agentic tasks, Gemini 3.7 Flash or Gemini 3.8 Flash?
The published evidence does not provide a shared weighted agentic tasks basis for both models, so BenchLM does not name a agentic tasks winner.
Which costs less, Gemini 3.7 Flash or Gemini 3.8 Flash?
For the stated presets, chat costs $0.00263 on Gemini 3.7 Flash and $0.00263 on Gemini 3.8 Flash; repository review costs $0.04875 and $0.04875; the cache-heavy agent loop costs $0.0675 and $0.0675. Costs use the listed standard API rates.
Which has the larger context window, Gemini 3.7 Flash or Gemini 3.8 Flash?
Both models list the same context window, 1M.
Related comparisons
Last updated September 2, 2026
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