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BenchLM
Data

Data as of October 17, 2026 · How the score is built

Superseded.Google has newer models in this line:Gemini 3.5 Flash-Lite
SupersededProprietaryNon-Reasoning

Released Mar 3, 20261M context

Gemini 3.1 Flash-Lite

Decision readingGemini 3.1 Flash-Lite scores 47 out of 100 and ranks #111 of 224. This profile shows 11 source-displayable benchmark rows; its strongest eligible category is Knowledge at #89. API pricing is $0.25 input and $1.5 output per million tokens, with cached input at $0.025.

Released Mar 3, 2026 — see all recent releases

Decision snapshot

Each value carries a field reference instead of floating alone. Markers compare this model with the current ranked and priced catalog; they are not absolute quality thresholds.

Capability

47/100

field median 49.6#111 of 224 ranked models

Public

#111of 224

Verified —

Price

$0.25input / $1.50 output

input median $0.75cached $0.025 · batch + cache $0.013 · blended $0.88

Speed

376tok/s

field median 92 tok/sFirst token 4.25 s

Context

1Mtokens

field median 256,000Maximum output length is tracked separately

Strongest published evidence

Knowledge ranks #89. Particularly effective for knowledge-intensive tasks like research, analysis, and factual Q&A.

Validate before choosing

11 published rows leave some tracked benchmark slots empty. Coding is its lowest eligible category at #101.

Source-linked · 11 displayable benchmark rows

Category score record

Scores and ranks appear only where published evidence can be displayed. The table keeps the score, weight, cohort, and evidence state together.

Category scores, ranks, weighting, benchmark coverage, and evidence status
CategoryScore
AgenticRank #100 of 128Percentile 22ndWeight 22%2 benchmarksVerified
27.4
CodingRank #101 of 150Percentile 33rdWeight 20%3 benchmarksVerified
27.2
ReasoningWeight 17%2 benchmarksVerified
Score pending
MultimodalRank Not rankedWeight 12%1 benchmarkVerified
42.0
KnowledgeRank #89 of 184Percentile 52ndWeight 12%2 benchmarksVerified
46.9
MultilingualWeight 7%0 benchmarksNot measured
Not measured
Inst. FollowingWeight 5%0 benchmarksNot measured
Not measured
MathRank Not rankedWeight 5%1 benchmarkVerified
44.0

11 of 681 tracked benchmark slots have displayable evidence · bars run 0–100

Coverage details

How much of this is verified

Coverage is split by category so a strong number never hides a thin evidence base. Verified means the row is tied to a published source; provisional rows remain visible but separate.

  1. Agentic2/2 verified
  2. Coding3/3 verified
  3. Reasoning2/2 verified
  4. Multimodal1/1 verified
  5. Knowledge2/2 verified
  6. MultilingualNot measured
  7. Inst. FollowingNot measured
  8. Math1/1 verified
Verified sourceProvisionalNot measured

Capability shape

Each axis shows percentile within that category’s eligible cohort. The comparison outline is the median of the six nearest public-score peers; a collapsed vertex means the category is not rank-eligible.

Gemini 3.1 Flash-Lite category percentile values

  • Agentic22nd percentile
  • Coding33rd percentile
  • ReasoningNot eligible
  • MultimodalNot eligible
  • Knowledge52nd percentile
  • MultilingualNot eligible
  • Instruction followingNot eligible
  • MathNot eligible

The dashed outline is median of 6 nearest peers.

Eligible category ranks

  1. Agentic#100/128
  2. Coding#101/150
  3. ReasoningNot ranked
  4. MultimodalNot ranked
  5. Knowledge#89/184
  6. MultilingualNot ranked
  7. Inst. FollowingNot ranked
  8. MathNot ranked
Top decileTop quartileMid-fieldNot eligible

Benchmark ledger

Coding opens by default. The marker compares each value with the best source-verified result in the catalog; provisional leaders do not set the reference. Expand the remaining categories for every published row.

Coding3 rows
Coding benchmark values, best verified comparison, weight, and source status
LiveCodeBench (Vals)LiveCodeBench, Vals AI runScore80.1%Versus best verified row

Best verified: Claude Fable 5.1 · 90.5%

Gap10.4 behindWeight8% ref. weight
Vibe Code BenchVibe Code Bench v1.1Score0.00%Versus best verified row

Best verified: Gemini 4 Argon · 91.90%

Gap91.9 behindWeightDisplay only
SWE-bench (Vals)SWE-bench, Vals AI runScore62.8%Versus best verified row

Best verified: Claude Opus 5 · 97.0%

Gap34.2 behindWeightDisplay only
Agentic2 rows
Agentic benchmark values, best verified comparison, weight, and source status
Terminal-Bench 2.1 (Vals)Terminal-Bench 2.1, Vals AI runScore34.1%Versus best verified row

Best verified: GPT-6 Astra · 87.3%

Gap53.2 behindWeight4% ref. weight
Gert LabsGert Labs Composite Game BenchmarkScore38.46%Versus best verified row

Best verified: Claude Opus 4.8 · 72.97%

Gap34.5 behindWeightDisplay only
Benchmark exact
Reasoning2 rows
Reasoning benchmark values, best verified comparison, weight, and source status
JevBench 1.4Score14.26Versus best verified row

Best verified: classifier.dev (fast) · 70.82

Gap56.6 behindWeightDisplay only
JevBench 1.5Score19.58Versus best verified row

Best verified: classifier.dev (fast) · 74.66

Gap55.1 behindWeightDisplay only
Multimodal1 row
Multimodal benchmark values, best verified comparison, weight, and source status
CharXivCharXiv ReasoningScore73.2%Versus best verified row

Best verified: Qwen3.8 Max · 93.5%

Gap20.3 behindWeightWeighted 20%
Knowledge2 rows
Knowledge benchmark values, best verified comparison, weight, and source status
MMLU-Pro (Vals)MMLU-Pro, Vals AI runScore86.2%Versus best verified row

Best verified: Claude Fable 5.1 · 92.4%

Gap6.2 behindWeight6% ref. weight
GPQA Diamond (Vals)GPQA Diamond, Vals AI runScore81.1%Versus best verified row

Best verified: Gemini 3.1 Pro · 95.5%

Gap14.4 behindWeight2% ref. weight
Math1 row
Math benchmark values, best verified comparison, weight, and source status
FrontierMath v2 (Tiers 1-3)FrontierMath v2 Tiers 1-3Score27.719%Versus best verified row

Best verified: GPT-6 Astra · 93.684%

Gap66 behindWeightWeighted 30%

What it costs to get this score

Published API price against the public score. The x-axis uses a log scale; the dashed path marks models that are not beaten by a cheaper, higher-scoring option. Price uses average of published input and output rates.

Current modelExplore all models

Gemini 3.1 Flash-Lite · 47.0 score · $0.88 blended per million tokens

The chart opens on the current model. Scroll horizontally to inspect the full price axis.

405060708090100$0.10$0.50$1$5$10$25$50$100↘ frontierGemini 3.1 Flash-Lite

Horizontal: blended price per million tokens, log scale · Vertical: public score

Lineage

The sequence follows explicit supersedes links. Each score is estimated for that model; a relative can inform a sparse estimate but never sets a floor, so a newer release can score below an earlier one. Scores and prices remain blank when the corresponding public row or first-party rate is unavailable.

  1. Mar 3, 2026 · you are here

    Gemini 3.1 Flash-Lite

    Score 47.0 · $0.25 / $1.5

  2. Jul 21, 2026

    Gemini 3.5 Flash-Lite

    Score 49.6 · $0.3 / $2.5

Base entry

Spec sheet

Each documented value carries its source. Missing fields stay visible as not sourced or not published, rather than disappearing from the page.

API model ID
gemini-3.1-flash-liteGoogle Gemini API pricing
Maximum output
Not sourced yet
Knowledge cutoff
Not sourced yet
Input modalities
Not sourced yet
Output modalities
Not sourced yet
Parameters
Not disclosed by the provider
Availability
Not sourced yet
Cloud regions
Not tracked yet
Lifecycle
Superseded
API capabilities
Tool calling, structured outputs, and batch support are not tracked yet
Prompt caching
Published at $0.025 per million cached input tokensGoogle Gemini API pricing
Self-host
Weights are not published
Rate limits
Not tracked yet

How to read this profile

The visual layer above carries the decisions. These notes preserve the model, ranking, coverage, and family context behind the numbers.

Gemini 3.1 Flash-Lite ranks #111 of 224 on the public leaderboard with a score of 46.96/100. It does not yet have enough sourced coverage for a verified position.

Gemini 3.1 Flash-Lite is a proprietary model with a 1M context window. No explicit reasoning mode is documented in this profile.

11 of 681 tracked benchmark slots currently have displayable evidence. Missing categories stay blank.

Its strongest eligible category is Knowledge at #89, while its lowest eligible position is Coding at #101. particularly effective for knowledge-intensive tasks like research, analysis, and factual Q&A.

Last updated October 17, 2026. Runtime fields remain blank until a sourced snapshot exists.

Questions

How does Gemini 3.1 Flash-Lite perform overall in AI benchmarks?

Gemini 3.1 Flash-Lite ranks #111 out of 224 models on the public BenchAlign leaderboard, with a score of 46.96/100. Its evidence status is Estimated, and this profile shows 11 source-displayable benchmark rows. The label describes evidence depth, not a provider quality claim; inspect category rows before choosing a workload.

Is Gemini 3.1 Flash-Lite good for knowledge and understanding?

Gemini 3.1 Flash-Lite ranks #89 out of 184 eligible models for knowledge and understanding, with a public category score of 46.9/100. Higher-ranked alternatives are available for workloads where this category decides the choice. Check the underlying rows before treating the aggregate as a workload guarantee.

Is Gemini 3.1 Flash-Lite good for coding and programming?

Gemini 3.1 Flash-Lite ranks #101 out of 150 eligible models for coding and programming, with a public category score of 27.2/100. Higher-ranked alternatives are available for workloads where this category decides the choice. Check the underlying rows before treating the aggregate as a workload guarantee.

Is Gemini 3.1 Flash-Lite good for mathematics?

Gemini 3.1 Flash-Lite has source-displayable benchmark coverage for mathematics, but the public category table does not assign it a rank there. The individual rows remain available for inspection. A missing category position means the evidence threshold was not met; it does not convert the model's unmeasured work into a zero.

Is Gemini 3.1 Flash-Lite good for reasoning and logic?

Gemini 3.1 Flash-Lite has source-displayable benchmark coverage for reasoning and logic, but the public category table does not assign it a rank there. The individual rows remain available for inspection. A missing category position means the evidence threshold was not met; it does not convert the model's unmeasured work into a zero.

Is Gemini 3.1 Flash-Lite good for agentic tool use and computer tasks?

Gemini 3.1 Flash-Lite ranks #100 out of 128 eligible models for agentic tool use and computer tasks, with a public category score of 27.4/100. Higher-ranked alternatives are available for workloads where this category decides the choice. Check the underlying rows before treating the aggregate as a workload guarantee.

Is Gemini 3.1 Flash-Lite good for multimodal and grounded tasks?

Gemini 3.1 Flash-Lite has source-displayable benchmark coverage for multimodal and grounded tasks, but the public category table does not assign it a rank there. The individual rows remain available for inspection. A missing category position means the evidence threshold was not met; it does not convert the model's unmeasured work into a zero.

Does Gemini 3.1 Flash-Lite have full benchmark coverage on BenchLM?

No. Gemini 3.1 Flash-Lite currently has 11 source-displayable rows across 681 tracked benchmark slots. The profile exposes published, non-generated evidence and leaves missing categories blank until an exact evaluation is available. Coverage describes how much was measured; it is not a penalty added to an individual benchmark result.

What is the context window size of Gemini 3.1 Flash-Lite?

Gemini 3.1 Flash-Lite has a documented context window of 1M. That figure is the maximum combined prompt and retained-conversation space reported for this exact model; it is not the maximum output length. The profile keeps output limits separate because providers often publish those limits independently.

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Compare Gemini 3.1 Flash-Lite with every tracked model953 comparisons