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BenchLM
Google logo
Model A
Gemini 3.1 Flash-Lite

Google

56.19/100

Supported · Public rank #89

90% interval 43.7–68.7

Gemini 3.1 Flash-Lite vs GPT-5.4 mini

Updated September 10, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.

OpenAI logo
Model B
GPT-5.4 mini

OpenAI

61.11/100

Supported · Public rank #59

90% interval 51.0–71.2

Decision reading

GPT-5.4 mini has the higher public score estimate, 61.11 versus 56.19, but the 90% score intervals overlap. Treat that as a lead, not a settled winner.

6 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 3.1 Flash-Lite

    Gemini 3.1 Flash-Lite has the larger documented context window.

    Confidence: documented

  • Chat turn cost

    1K fresh input + 500 output tokens

    Gemini 3.1 Flash-Lite

    Gemini 3.1 Flash-Lite has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.

    Confidence: listed-rates

  • Cache-heavy agent loop cost

    200K cached + 20K fresh input + 10K output tokens

    Gemini 3.1 Flash-Lite

    Gemini 3.1 Flash-Lite has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.

    Confidence: listed-rates

Show secondary and unsupported calls

  • Repository review cost

    50K fresh input + 3K output tokens

    Gemini 3.1 Flash-Lite

    Gemini 3.1 Flash-Lite has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.

    Confidence: listed-rates

  • Coding work

    Code generation, repair, and software-engineering tasks

    Not enough matched evidence

    Gemini 3.1 Flash-Lite is scored on Estimated evidence for coding, so the reading is directional rather than like-for-like.

    Confidence: limited

  • Agentic work

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

    Not enough matched evidence

    Gemini 3.1 Flash-Lite and GPT-5.4 mini are scored on Estimated evidence for agentic, so the reading is directional rather than like-for-like.

    Confidence: limited

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
6
Gemini 3.1 Flash-Lite only
2
GPT-5.4 mini only
13
Like-for-like categories
0 / 8

3 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.

Agentic

Directional only
Gemini 3.1 Flash-Lite
42.9
Estimated · #101/152
GPT-5.4 mini
39.1
Estimated · #119/152
Basis
BenchAlign lane · 2 vs 6 public rows
Reading
Directional only

Coding

Directional only
Gemini 3.1 Flash-Lite
37.9
Estimated · #124/151
GPT-5.4 mini
42.7
Supported · #104/151
Basis
BenchAlign lane · 3 vs 4 public rows
Reading
Directional only

Knowledge

Directional only
Gemini 3.1 Flash-Lite
51.5
Estimated · #71/183
GPT-5.4 mini
55.6
Supported · #52/183
Basis
BenchAlign lane · 2 vs 5 public rows
Reading
Directional only

Reasoning

Not comparable
Gemini 3.1 Flash-Lite
Not ranked
GPT-5.4 mini
73.9
Unranked · 2 rankable rows
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Math

Not comparable
Gemini 3.1 Flash-Lite
Not ranked
GPT-5.4 mini
44.5
Unranked · 2 rankable rows
Basis
Provisional lane · 0 vs 2 weighted rows
Reading
Not comparable

Multilingual

Not comparable
Gemini 3.1 Flash-Lite
Not ranked
GPT-5.4 mini
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Multimodal

Not comparable
Gemini 3.1 Flash-Lite
37.5
Unranked · 1 rankable row
GPT-5.4 mini
57.2
#31/48
Basis
Provisional lane · 1 vs 1 weighted rows
Reading
Not comparable

Instruction following

Not comparable
Gemini 3.1 Flash-Lite
Not ranked
GPT-5.4 mini
89.8
#23/123
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.

Too few matched category axes support a radar. The ruled list below shows only shared benchmark results; positions use each benchmark’s normalized display scale when available.

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 3.1 Flash-Lite
$0.001
Fits in one request
GPT-5.4 mini
$0.003
Fits in one request

Gemini 3.1 Flash-Lite has the lower modeled cost

Costs use the listed standard API rates.

Repository review

50K fresh input + 3K output tokens

Gemini 3.1 Flash-Lite
$0.017
Fits in one request
GPT-5.4 mini
$0.051
Fits in one request

Gemini 3.1 Flash-Lite has the lower modeled cost

Costs use the listed standard API rates.

Cache-heavy agent loop

200K cached + 20K fresh input + 10K output tokens

Gemini 3.1 Flash-Lite
$0.025
Fits in one request
GPT-5.4 mini
$0.075
Fits in one request

Gemini 3.1 Flash-Lite has the lower modeled cost

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.

Cached-input rate

A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.

Gemini 3.1 Flash-Lite

$0.025 per 1M cached input tokens

Google Gemini API pricing

GPT-5.4 mini

$0.075 per 1M cached input tokens

OpenAI pricing

Provider availability

Gemini 3.1 Flash-Lite

Not sourced

GPT-5.4 mini

Generally Available · OpenAI Responses API

OpenAI model catalog

Reasoning profile

Gemini 3.1 Flash-Lite

Non-Reasoning

GPT-5.4 mini

Reasoning

Weight access

Gemini 3.1 Flash-Lite

Proprietary

GPT-5.4 mini

Proprietary

License

Gemini 3.1 Flash-Lite

Proprietary

GPT-5.4 mini

Proprietary

Release date

Gemini 3.1 Flash-Lite

2026-03-03

GPT-5.4 mini

2026-03-17

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
GPT-5.4 mini has the higher public score estimate, 61.11 versus 56.19, but the 90% score intervals overlap.
Workload cost
Repository review: $0.017 vs $0.051. Cache-heavy agent loop: $0.025 vs $0.075.
Context tradeoff
Gemini 3.1 Flash-Lite has the larger documented window (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 evidence21 rows

Agentic

  • Gert Labs

    Gemini 3.1 Flash-Lite38.46%
    Source
    GPT-5.4 mini—

    Not directly comparable

  • Terminal-Bench 2.1 (Vals)

    Gemini 3.1 Flash-Lite34.1%
    Source
    GPT-5.4 mini54.7%
    Source

    GPT-5.4 mini leads this result

  • Terminal-Bench 2.0

    Gemini 3.1 Flash-Lite—
    GPT-5.4 mini60%
    Source

    Not directly comparable

  • OSWorld-Verified

    Gemini 3.1 Flash-Lite—
    GPT-5.4 mini72.1%
    Source

    Not directly comparable

  • MCP Atlas

    Gemini 3.1 Flash-Lite—
    GPT-5.4 mini57.7%
    Source

    Not directly comparable

  • Toolathlon

    Gemini 3.1 Flash-Lite—
    GPT-5.4 mini42.9%
    Source

    Not directly comparable

  • τ²-bench results

    Gemini 3.1 Flash-Lite—
    GPT-5.4 mini93.4%
    Source

    Not directly comparable

Coding

  • Vibe Code Bench

    Shared source
    Gemini 3.1 Flash-Lite0.00%
    GPT-5.4 mini47.97%

    GPT-5.4 mini leads this result

  • LiveCodeBench (Vals)

    Gemini 3.1 Flash-Lite80.1%
    Source
    GPT-5.4 mini81.5%
    Source

    GPT-5.4 mini leads this result

  • SWE-bench (Vals)

    Gemini 3.1 Flash-Lite62.8%
    Source
    GPT-5.4 mini73.0%
    Source

    GPT-5.4 mini leads this result

  • FrontierCode 1.1 Main

    Gemini 3.1 Flash-Lite—
    GPT-5.4 mini27.0%
    Source

    Not directly comparable

Knowledge

  • GPQA Diamond (Vals)

    Gemini 3.1 Flash-Lite81.1%
    Source
    GPT-5.4 mini83.1%
    Source

    GPT-5.4 mini leads this result

  • MMLU-Pro (Vals)

    Gemini 3.1 Flash-Lite86.2%
    Source
    GPT-5.4 mini84.6%
    Source

    Gemini 3.1 Flash-Lite leads this result

  • GPQA

    Gemini 3.1 Flash-Lite—
    GPT-5.4 mini88%
    Source

    Not directly comparable

  • HLE

    Gemini 3.1 Flash-Lite—
    GPT-5.4 mini41.5%
    Source

    Not directly comparable

  • HLE w/o tools

    Gemini 3.1 Flash-Lite—
    GPT-5.4 mini28.2%
    Source

    Not directly comparable

Math

  • FrontierMath v2 (Tiers 1-3)

    Gemini 3.1 Flash-Lite—
    GPT-5.4 mini28.280%
    Source

    Not directly comparable

  • FrontierMath v2 (Tier 4)

    Gemini 3.1 Flash-Lite—
    GPT-5.4 mini2.080%
    Source

    Not directly comparable

Multimodal

  • CharXiv

    Gemini 3.1 Flash-Lite73.2%
    Source
    GPT-5.4 mini—

    Not directly comparable

  • MMMU-Pro

    Gemini 3.1 Flash-Lite—
    GPT-5.4 mini76.6%
    Source

    Not directly comparable

  • MMMU-Pro w/ Python

    Gemini 3.1 Flash-Lite—
    GPT-5.4 mini78%
    Source

    Not directly comparable

Frequently asked questions

Which is better, Gemini 3.1 Flash-Lite or GPT-5.4 mini?

GPT-5.4 mini has the higher public score estimate, 61.11 versus 56.19, 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 3.1 Flash-Lite or GPT-5.4 mini?

GPT-5.4 mini scores higher for coding on the public lane, 42.7 to 37.9. Gemini 3.1 Flash-Lite is scored on Estimated evidence for coding, so the reading is directional rather than like-for-like. BenchLM does not name a winner for coding from a directional reading; read the shared benchmark rows directly and test the models on the same task set.

Which is better for agentic tasks, Gemini 3.1 Flash-Lite or GPT-5.4 mini?

Gemini 3.1 Flash-Lite scores higher for agentic tasks on the public lane, 42.9 to 39.1. Gemini 3.1 Flash-Lite and GPT-5.4 mini are 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 3.1 Flash-Lite or GPT-5.4 mini?

For the stated presets, chat costs $0.001 on Gemini 3.1 Flash-Lite and $0.003 on GPT-5.4 mini; repository review costs $0.017 and $0.051; the cache-heavy agent loop costs $0.025 and $0.075. Costs use the listed standard API rates.

Which has the larger context window, Gemini 3.1 Flash-Lite or GPT-5.4 mini?

Gemini 3.1 Flash-Lite has the larger documented context window: 1M, compared with 400K.

Related comparisons

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Last updated September 10, 2026

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