Gemini 3.7 Flash vs Gemma 4 26B A4B

Updated September 27, 2026. Rank says Gemini 3.7 Flash is ahead. Price, access, and your workload can each overturn that. Public scores include evidence status and uncertainty.

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.

Model A

Gemini 3.7 Flash

Google

67.66/100

Supported · Public rank #19

90% interval 63.0–72.3

Model B

Gemma 4 26B A4B

Google

46.28/100

Supported · Public rank #90

90% interval 31.9–60.7

Shared results: 0
Gemini 3.7 Flash only: 25
Gemma 4 26B A4B only: 4
Like-for-like categories: 2 / 8

Supported: Gemini 3.7 Flash and Gemma 4 26B A4BHow the comparison works

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 3.7 Flash
Gemini 3.7 Flash leads on the public coding lane, 60.3 to 34.3, with Supported evidence for both models and non-overlapping 90% intervals.
Confidence: stronger
Long documents
Prompts that approach the documented context limit
Gemini 3.7 Flash
Gemini 3.7 Flash has the larger documented context window.
Confidence: documented

Show secondary and unsupported calls

Agentic work
Tool use, computer use, and multi-step task completion
Not enough matched evidence
Gemma 4 26B A4B is not ranked on the public lane for agentic, so no winner is named for agentic.
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

Which one for a specific job

Choose a job from the LLM Selector's task catalog to see the category row it rests on, under the same basis rules as the table below. A directional row stays directional; choosing a job never creates a winner.

Pick the job you would use them for

The same task catalog as the LLM Selector. Each job names the evidence surface it rests on; nothing here adds a new score.

60.3Gemini 3.7 Flash34.3Gemma 4 26B A4B

Like-for-like · BenchAlign v5.7

Gemini 3.7 Flash leads the like-for-like coding row.

Coding scores combine specific tasks and setups. Match the editor, harness, and effort to your workflow.

Open the coding leaderboard Shortlist models for this job

Same basis rules as the category table below

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.

Category results, on a stated basis

Each row shows the public-lane category score for both models: the BenchAlign v5.7 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 3.7 Flash: 60.3; Supported · #17/135
Gemma 4 26B A4B: 34.3; Supported · #77/135
Basis: BenchAlign v5.7 lane · 6 vs 0 public rows
Reading: Gemini 3.7 Flash leads

Knowledge

Like-for-like

Gemini 3.7 Flash: 71.1; Supported · #10/158
Gemma 4 26B A4B: 36.4; Supported · #101/158
Basis: BenchAlign v5.7 lane · 6 vs 3 public rows
Reading: Gemini 3.7 Flash leads

Multimodal

Directional only

Gemini 3.7 Flash: 82.6; #10/50
Gemma 4 26B A4B: 44.2; #43/50
Basis: Provisional lane · 1 vs 1 weighted rows
Reading: Directional only

Agentic

Not comparable

Gemini 3.7 Flash: 58.6; Supported · #20/105
Gemma 4 26B A4B: Not ranked
Basis: BenchAlign v5.7 lane · 7 vs 0 public rows
Reading: Not comparable

Reasoning

Not comparable

Gemini 3.7 Flash: 77.8; Unranked · 5 rankable rows
Gemma 4 26B A4B: 67.2; Unranked · 2 rankable rows
Basis: Provisional lane · 1 vs 0 weighted rows
Reading: Not comparable

Multilingual

Not comparable

Gemini 3.7 Flash: Not ranked
Gemma 4 26B A4B: Not ranked
Basis: Provisional lane · 0 vs 0 weighted rows
Reading: Not comparable

Instruction following

Not comparable

Gemini 3.7 Flash: Not ranked
Gemma 4 26B A4B: 87.3; #31/124
Basis: Provisional lane · 0 vs 0 weighted rows
Reading: Not comparable

Math

Not comparable

Gemini 3.7 Flash: Not ranked
Gemma 4 26B A4B: Not ranked
Basis: Provisional lane · 0 vs 0 weighted rows
Reading: Not comparable

Category scores with the server-provided evidence basis for Gemini 3.7 Flash and Gemma 4 26B A4B
Category	Gemini 3.7 Flash	Gemma 4 26B A4B	Basis	Reading
Coding	60.3Supported · #17/135	34.3Supported · #77/135	Like-for-likeBenchAlign v5.7 lane · 6 vs 0 public rows	Gemini 3.7 Flash leads
Knowledge	71.1Supported · #10/158	36.4Supported · #101/158	Like-for-likeBenchAlign v5.7 lane · 6 vs 3 public rows	Gemini 3.7 Flash leads
Multimodal	82.6#10/50	44.2#43/50	Directional onlyProvisional lane · 1 vs 1 weighted rows	Directional only
Agentic	58.6Supported · #20/105	Not ranked	Not comparableBenchAlign v5.7 lane · 7 vs 0 public rows	Not comparable
Reasoning	77.8Unranked · 5 rankable rows	67.2Unranked · 2 rankable rows	Not comparableProvisional lane · 1 vs 0 weighted rows	Not comparable
Multilingual	Not ranked	Not ranked	Not comparableProvisional lane · 0 vs 0 weighted rows	Not comparable
Instruction following	Not ranked	87.3#31/124	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

Ranks count the models scored in each category’s lane, so the agentic, coding, and knowledge denominators (BenchAlign v5.7) differ from the provisional-lane categories. Unranked scores sit on the provisional lane’s scale but never name a winner. Like-for-like rows within 0.5 points read as a practical tie.

Supported evidence per lane · bars run 0–100Methodology

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
Gemma 4 26B A4B: Self-hosted; infrastructure cost varies; Fits in one request

Gemma 4 26B A4B 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
Gemma 4 26B A4B: Self-hosted; infrastructure cost varies; Fits in one request

Gemma 4 26B A4B 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
Gemma 4 26B A4B: Self-hosted; infrastructure cost varies; Fits in one request; Cached-input rate unavailable

Reasoning

Gemma 4 26B A4B

Reasoning

Weight access

Gemini 3.7 Flash

Proprietary

Gemma 4 26B A4B

Open Weight

License

Gemini 3.7 Flash

Proprietary

Gemma 4 26B A4B

Open Weight

Release date

Gemini 3.7 Flash

2026-08-13

Gemma 4 26B A4B

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 3.7 Flash has the larger documented window (1M).

Run the same representative tasks against both endpoints before changing production traffic.

Questions

Which is better, Gemini 3.7 Flash or Gemma 4 26B A4B?

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 Gemma 4 26B A4B?

Gemini 3.7 Flash leads the public coding lane, 60.3 to 34.3, with Supported evidence for both models and non-overlapping 90% intervals.

Which is better for agentic tasks, Gemini 3.7 Flash or Gemma 4 26B A4B?

Gemma 4 26B A4B 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 Gemma 4 26B A4B?

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 Gemma 4 26B A4B?

Gemini 3.7 Flash has the larger documented context window: 1M, compared with 256K.

Benchmark evidence

The full public result ledger is available for audit without forcing a wide desktop table onto a phone.

Browse raw public benchmark evidence29 rows

Agentic

Terminal-Bench 2.1
Gemini 3.7 Flash85.8%
Source
Gemma 4 26B A4B—
Not directly comparable
Terminal-Bench 3.0
Gemini 3.7 Flash14.9%
Source
Gemma 4 26B A4B—
Not directly comparable
AutomationBench
Gemini 3.7 Flash30.4%
Source
Gemma 4 26B A4B—
Not directly comparable
OSWorld 2.0
Gemini 3.7 Flash47.9%
Source
Gemma 4 26B A4B—
Not directly comparable
Agents' Last Exam
Gemini 3.7 Flash26.3%
Source
Gemma 4 26B A4B—
Not directly comparable
Terminal-Bench 2.1 (Vals)
Gemini 3.7 Flash77.5%
Source
Gemma 4 26B A4B—
Not directly comparable
ApprenticeBench
Gemini 3.7 Flash16%
Source
Gemma 4 26B A4B—
Not directly comparable

Coding

FrontierCode 1.1 Main
Gemini 3.7 Flash43.6%
Source
Gemma 4 26B A4B—
Not directly comparable
DeepSWE
Gemini 3.7 Flash65.3%
Source
Gemma 4 26B A4B—
Not directly comparable
Terminal-Bench 2.1
Gemini 3.7 Flash85.8%
Source
Gemma 4 26B A4B—
Not directly comparable
FrontierSWE v2
Gemini 3.7 Flash20.3%
Source
Gemma 4 26B A4B—
Not directly comparable
LiveCodeBench (Vals)
Gemini 3.7 Flash88.7%
Source
Gemma 4 26B A4B—
Not directly comparable
SWE-bench (Vals)
Gemini 3.7 Flash80.8%
Source
Gemma 4 26B A4B—
Not directly comparable

Reasoning

MRCR v2 64K-128K
Gemini 3.7 Flash97%
Source
Gemma 4 26B A4B—
Not directly comparable
ARC-AGI-1
Gemini 3.7 Flash95.50%
Source
Gemma 4 26B A4B—
Not directly comparable
ARC-AGI-2
Gemini 3.7 Flash84.6%
Source
Gemma 4 26B A4B—
Not directly comparable

Multimodal

CharXiv w/o tools
Gemini 3.7 Flash84.5%
Source
Gemma 4 26B A4B—
Not directly comparable
CharXiv
Gemini 3.7 Flash88.7%
Source
Gemma 4 26B A4B—
Not directly comparable
LVBench
Gemini 3.7 Flash85.4%
Source
Gemma 4 26B A4B—
Not directly comparable
MMMU-Pro
Gemini 3.7 Flash—
Gemma 4 26B A4B73.8%
Source
Not directly comparable

Knowledge

HLE-Verified
Gemini 3.7 Flash53.6%
Source
Gemma 4 26B A4B—
Not directly comparable
LABBench2
Gemini 3.7 Flash82.1%
Source
Gemma 4 26B A4B—
Not directly comparable
BioMysteryBench (human-solvable)
Gemini 3.7 Flash87.1%
Source
Gemma 4 26B A4B—
Not directly comparable
BioMysteryBench (human-difficult)
Gemini 3.7 Flash43.5%
Source
Gemma 4 26B A4B—
Not directly comparable
GPQA Diamond (Vals)
Gemini 3.7 Flash93.9%
Source
Gemma 4 26B A4B—
Not directly comparable
MMLU-Pro (Vals)
Gemini 3.7 Flash90.1%
Source
Gemma 4 26B A4B—
Not directly comparable
MMLU-Pro
Gemini 3.7 Flash—
Gemma 4 26B A4B82.6%
Source
Not directly comparable
HLE
Gemini 3.7 Flash—
Gemma 4 26B A4B17.2%
Source
Not directly comparable
HLE w/o tools
Gemini 3.7 Flash—
Gemma 4 26B A4B8.7%
Source
Not directly comparable

29 public results · 0 shared

Related comparisons

Compare API pricing Read the methodology Open the model selector

Watch Gemini 3.7 Flash vs Gemma 4 26B A4B

One weekly email when material rank, price, or benchmark evidence changes make this matchup worth revisiting.

Read a sample issue

Join 2,000+ readers.

Last updated September 27, 2026

Gemini 3.7 Flash vs Gemma 4 26B A4B

Decision reading

Which one for your work

Coding work

Long documents

Agentic work

Chat turn cost

Cache-heavy agent loop cost

Repository review cost

Which one for a specific job

What is actually comparable

Shape of the matched evidence

Category results, on a stated basis

Coding

Knowledge

Multimodal

Agentic

Reasoning

Multilingual

Instruction following

Math

What each workload costs

Chat turn

Repository review

Cache-heavy agent loop

Specification differences

Context window

API model ID

Cached-input rate

Documented inputs

Documented outputs

Provider availability

Reasoning profile

Weight access

License

Release date

If you already use one of these models

Questions

Which is better, Gemini 3.7 Flash or Gemma 4 26B A4B?

Which is better for coding, Gemini 3.7 Flash or Gemma 4 26B A4B?

Which is better for agentic tasks, Gemini 3.7 Flash or Gemma 4 26B A4B?

Which costs less, Gemini 3.7 Flash or Gemma 4 26B A4B?

Which has the larger context window, Gemini 3.7 Flash or Gemma 4 26B A4B?

Benchmark evidence

Agentic

Coding

Reasoning

Multimodal

Knowledge

Related comparisons

Watch Gemini 3.7 Flash vs Gemma 4 26B A4B