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Model A
Gemini 3.5 Flash-Lite

Google

60.5/100

Supported · Public rank #72

90% interval 49.072.0

Gemini 3.5 Flash-Lite vs Gemma 4 31B

Updated September 4, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.

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Model B
Gemma 4 31B

Google

58.69/100

Supported · Public rank #83

90% interval 42.874.6

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.

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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.

  • Long documents

    Prompts that approach the documented context limit

    Gemini 3.5 Flash-Lite

    Gemini 3.5 Flash-Lite has the larger documented context window.

    Confidence: documented

Show secondary and unsupported calls
  • Coding work

    Code generation, repair, and software-engineering tasks

    No clear pick

    The like-for-like coding result is a practical tie on the public lane (within 0.5 points).

    Confidence: limited

  • Agentic work

    Tool use, computer use, and multi-step task completion

    Not enough matched evidence

    Gemini 3.5 Flash-Lite is scored on Estimated evidence for agentic, so the reading is directional rather than like-for-like.

    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.

Shared results
0
Gemini 3.5 Flash-Lite only
10
Gemma 4 31B only
8
Like-for-like categories
2 / 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.

Coding

Like-for-like
Gemini 3.5 Flash-Lite
43.6
Supported · #121/183
Gemma 4 31B
43.5
Supported · #124/183
Basis
BenchAlign lane · 4 vs 2 public rows
Reading
Practical tie

Knowledge

Like-for-like
Gemini 3.5 Flash-Lite
53.0
Supported · #71/181
Gemma 4 31B
47.8
Supported · #104/181
Basis
BenchAlign lane · 2 vs 4 public rows
Reading
Gemini 3.5 Flash-Lite leads · intervals overlap

Agentic

Directional only
Gemini 3.5 Flash-Lite
43.4
Estimated · #104/151
Gemma 4 31B
27.6
Supported · #140/151
Basis
BenchAlign lane · 3 vs 1 public rows
Reading
Directional only

Multimodal

Directional only
Gemini 3.5 Flash-Lite
76.1
#16/48
Gemma 4 31B
57.8
#30/48
Basis
Provisional lane · 0 vs 1 weighted rows
Reading
Directional only

Reasoning

Not comparable
Gemini 3.5 Flash-Lite
60.8
Unranked · 3 rankable rows
Gemma 4 31B
70.1
Unranked · 2 rankable rows
Basis
Provisional lane · 1 vs 0 weighted rows
Reading
Not comparable

Math

Not comparable
Gemini 3.5 Flash-Lite
Not ranked
Gemma 4 31B
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Multilingual

Not comparable
Gemini 3.5 Flash-Lite
Not ranked
Gemma 4 31B
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Instruction following

Not comparable
Gemini 3.5 Flash-Lite
Not ranked
Gemma 4 31B
92.6
#12/120
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
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 3.5 Flash-Lite
$0.00155
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 3.5 Flash-Lite
$0.0225
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 3.5 Flash-Lite
$0.037
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.

Cached-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 pricing

Gemma 4 31B

No comparable hosted API rate

Reasoning profile

Gemini 3.5 Flash-Lite

Reasoning

Gemma 4 31B

Reasoning

Weight access

Gemini 3.5 Flash-Lite

Proprietary

Gemma 4 31B

Open Weight

License

Gemini 3.5 Flash-Lite

Proprietary

Gemma 4 31B

Open Weight

Release date

Gemini 3.5 Flash-Lite

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 3.5 Flash-Lite 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 3.5 Flash-Lite
API / mo$2,100
Self-host / moNot listed
Break-even
Proprietary model — self-hosting not applicable.
Gemma 4 31B
API / mo$0
Self-host / mo$429
Break-even
Model the full 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 evidence18 rows

Agentic

  • Terminal-Bench 2.0

    Gemini 3.5 Flash-Lite54%
    Source
    Gemma 4 31B

    Not directly comparable

  • OSWorld-Verified

    Gemini 3.5 Flash-Lite74%
    Source
    Gemma 4 31B

    Not directly comparable

  • Terminal-Bench 2.1 (Vals)

    Gemini 3.5 Flash-Lite50.2%
    Source
    Gemma 4 31B

    Not directly comparable

  • Gert Labs

    Gemini 3.5 Flash-Lite
    Gemma 4 31B35.26%
    Source

    Not directly comparable

Coding

  • Terminal-Bench 2.0

    Gemini 3.5 Flash-Lite54.0%
    Source
    Gemma 4 31B

    Not directly comparable

  • SWE-bench Pro

    Gemini 3.5 Flash-Lite54.2%
    Source
    Gemma 4 31B

    Not directly comparable

  • LiveCodeBench (Vals)

    Gemini 3.5 Flash-Lite79.0%
    Source
    Gemma 4 31B

    Not directly comparable

  • SWE-bench (Vals)

    Gemini 3.5 Flash-Lite75.0%
    Source
    Gemma 4 31B

    Not directly comparable

  • SWE-Rebench

    Gemini 3.5 Flash-Lite
    Gemma 4 31B41.6%
    Source

    Not directly comparable

  • React Native Evals

    Gemini 3.5 Flash-Lite
    Gemma 4 31B75.2%
    Source

    Not directly comparable

Reasoning

  • MRCRv2

    Gemini 3.5 Flash-Lite72.2%
    Source
    Gemma 4 31B

    Not directly comparable

Knowledge

  • GPQA Diamond (Vals)

    Gemini 3.5 Flash-Lite83.8%
    Source
    Gemma 4 31B

    Not directly comparable

  • MMLU-Pro (Vals)

    Gemini 3.5 Flash-Lite85.8%
    Source
    Gemma 4 31B

    Not directly comparable

  • GPQA

    Gemini 3.5 Flash-Lite
    Gemma 4 31B84.3%
    Source

    Not directly comparable

  • MMLU-Pro

    Gemini 3.5 Flash-Lite
    Gemma 4 31B85.2%
    Source

    Not directly comparable

  • HLE

    Gemini 3.5 Flash-Lite
    Gemma 4 31B26.5%
    Source

    Not directly comparable

  • HLE w/o tools

    Gemini 3.5 Flash-Lite
    Gemma 4 31B19.5%
    Source

    Not directly comparable

Multimodal

  • MMMU-Pro

    Gemini 3.5 Flash-Lite
    Gemma 4 31B76.9%
    Source

    Not directly comparable

Frequently asked questions

Which is better, Gemini 3.5 Flash-Lite 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 3.5 Flash-Lite or Gemma 4 31B?

The like-for-like coding row is a practical tie on the public lane, 43.6 against 43.5, inside the 0.5-point band BenchLM treats as level.

Which is better for agentic tasks, Gemini 3.5 Flash-Lite or Gemma 4 31B?

Gemini 3.5 Flash-Lite scores higher for agentic tasks on the public lane, 43.4 to 27.6. Gemini 3.5 Flash-Lite is scored on Estimated evidence for agentic tasks, so the reading is directional rather than like-for-like. BenchLM does not name a winner for agentic tasks from a directional reading; read the shared benchmark rows directly and test the models on the same task set.

Which costs less, Gemini 3.5 Flash-Lite 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 3.5 Flash-Lite or Gemma 4 31B?

Gemini 3.5 Flash-Lite has the larger documented context window: 1M, compared with 256K.

Related comparisons

Last updated September 4, 2026

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