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ModelCap

Gemma 4 31B

Arena #77Official publisher releaseOpen weightsFree tier7d #40 → #37

Google·#37 of 352 on the current board·cheaper than #36 Qwen3.7 Plus

Gemma 4 31B is a language model from Google. It ranks #37 of 352 on ModelCap's current board, with an Index score of 71.9, measured on 2 public benchmarks. Its score range of 66.4–77.4 spans positions #24–#59. It is listed at $0.20 per million input tokens and $0.40 per million output tokens across 16 providers. It reads up to 262K tokens of context, and its weights are openly downloadable.

Figures as of 6 Nov 2026, 13:52 UTC · download the public dataset · methodology

ModelCap Index · Current board
71.9#37
Measured on 2 public benchmarks · range 66.4–77.4
Evidence as of 28 Oct 2026, 00:00 UTC
Market Gravity
59.3Increased by 0.6
Secondary market signal
Input
$0.20
per 1M tokens
Output
$0.40
per 1M tokens
Context
262K
tokens
Providers
16
19 endpoints

Providers

Uptime measured over the last 30 minutes
ProviderInputOutputContextQuantUptime
ModalCheapest$0.34$0.10131K—100.0%
PrimeIntellectfp8$0.099$0.166262Kfp8100.0%
DeepInfrafp8/flex$0.16$0.32262Kfp8100.0%
CoreWeavefp4$0.10$0.34262Kfp4100.0%
Venicefp4$0.12$0.36256Kfp4100.0%
Chutesfp4$0.12$0.37131Kfp4100.0%
Crusoebf16$0.14$0.40262Kbf16100.0%
DeepInfrafp8$0.20$0.40262Kfp8100.0%
DekaLLM$0.14$0.40262K—100.0%
Friendli$0.14$0.40262K—100.0%
NextBitfp4$0.15$0.40262Kfp4100.0%
Novitabf16$0.14$0.40262Kbf16100.0%
Parasailfp8$0.15$0.40262Kfp8100.0%
DeepInfraturbo$0.135$0.51262Kfp4100.0%
DeepInfrafp8/priority$0.30$0.60262Kfp8100.0%
ModelRunfp4$0.75$1.00262Kfp4100.0%
SiliconFlowfp8$0.75$1.00262Kfp8100.0%
Io Net$0.361$1.09262K—100.0%
SambaNova$0.38$1.15131K—90.91%

Hugging Face Inference Providers

Exact repository identity

Provider economics and telemetry published by the Hugging Face Router. These are operational signals, not benchmark results.

ProviderInputOutputContextTTFTThroughputFeatures
deepinfra
live
$0.20$0.40262K370 ms37.3 tok/stools · structured
novita
live
$0.14$0.40262K476 ms29.4 tok/stools · structured
featherless-ai
live
——————

Reported evaluation leads (26)

Not independent measurement

Structured rows reported in this exact model repository at the pinned revision below. They are the publisher talking about itself: never measured evidence, never a score input on their own. They remain quarantined until dataset revision, harness, configuration and identity pass ModelCap’s independent admission review.

Dataset / taskMetricValueRevisionProvenance
joelniklaus/LEXam-hard
lexam_hard
—37.41
Pinned
1bd50ee3ac80286fed27e5b89f03f4d8b4494244
Reported
Quarantined
allenai/IFBench_test
prompt_level_loose
—76
Unpinned
not published
Reported
Quarantined
cais/hle
hle
—26.5
Unpinned
not published
Reported
Quarantined
facebook/mmi
mmi-value
—11.19
Unpinned
not published
Reported
Quarantined
facebook/mmi
modality-presence-score
—14.61
Unpinned
not published
Reported
Quarantined
facebook/mmi
error-rate
—41.1
Unpinned
not published
Reported
Quarantined
facebook/mmi
pass-rate-strict
—9.18
Unpinned
not published
Reported
Quarantined
facebook/mmi
pass-rate-lenient
—9.63
Unpinned
not published
Reported
Quarantined
facebook/mmi
recall
—13.29
Unpinned
not published
Reported
Quarantined
facebook/mmi
precision
—100
Unpinned
not published
Reported
Quarantined
Idavidrein/gpqa
diamond
—84.3
Unpinned
not published
Reported
Quarantined
LiquidAI/ifstruct-v1.0
ifstruct_v1
—95.9
Unpinned
not published
Reported
Quarantined
llamaindex/ParseBench
mean
—62.4
Unpinned
not published
Reported
Quarantined
llamaindex/ParseBench
text_content
—89.9
Unpinned
not published
Reported
Quarantined
llamaindex/ParseBench
text_formatting
—69.3
Unpinned
not published
Reported
Quarantined
llamaindex/ParseBench
layout
—57.4
Unpinned
not published
Reported
Quarantined
llamaindex/ParseBench
chart
—15
Unpinned
not published
Reported
Quarantined
llamaindex/ParseBench
table
—80.6
Unpinned
not published
Reported
Quarantined
MBZUAI/longshot-bench
overall
—38.87
Unpinned
not published
Reported
Quarantined
MBZUAI/longshot-bench
core_perception
—31.85
Unpinned
not published
Reported
Quarantined

Showing 20 of 26 rows.

Other versions (1)

ModelCap Index · Current board

Methodology
71.9
Measured on 2 public benchmarks
Current board
#37 of 352
Score range
66.4–77.4
Rank range
#24–#59
Evidence as of
28 Oct 2026, 00:00 UTC
Benchmarks used
Arena Coding, Arena Overall
Technical details
Public rank basis
Measured (measured)
Evidence label
Measured · 2 public benchmark observations across 2 boards
Index support
56.1% · strong
Identity binding
Exact catalogue product · google/google/gemma-4-31b-it · aggregates disclosed benchmark configurations · endpoint configuration not claimed · artifact metadata google/gemma-4-31B-it@842da3794eaa0b77d5f08bae87a17459d91ff475 (not the evaluation revision)
Index observations used
2
Qualified Index evidence point
71.9
Bayesian Evidence Score · measured evidence input only

BES normalizes admitted public benchmark evidence for measured Index rows. Its legacy score and observables prior do not define the public language rank.

Observed capability
71.9
Evidence status
confirmed · 75% mass
General preference
72.1
Coding
70.7
Agents & tools
—
Reasoning
—
Evidence breadth
92%
Evidence coverage
56%
Market and catalogue signals · secondary, never the language Index rank
Usage (OpenRouter popularity)
35.8
Liquidity (providers × uptime)
91.9
Open reach (HF downloads)
96.4
Surface (context / tools / modalities)
90.3
Freshness
43.6
  • · OpenRouter popularity #42
  • · 16 live providers
  • · HF 30d downloads 7526808
  • · Catalogue: context 262144, reasoning, tools, modalities Image/Text/Video
  • · First seen 2026-04-02

These adoption and deployment observations remain context only. They do not change this model's ModelCap Index score or rank.

BES evidence selected · measured input only

The bounded 0–100 capability score blends each source’s competitive placement with its published achievement, then combines capability families. Evidence breadth adds a modest uncertainty adjustment; price and popularity are not part of benchmark-led rank.

Deployment readiness

Metadata index
89.7
strong · 98% metadata coverage
Not capability
Artifact reproducibility
100.0
Access & legal clarity
100.0
Deployability
99.0
Evaluation provenance
50.0

Not yet published: pinned evaluation dataset versions.

A metadata completeness and deployability index—not a safety certification, quality grade, or production-readiness claim.

Market activity

Venue coverage
Market Gravity
59.3
OpenRouter weekly popularity
#42 of 339

Market Gravity uses OpenRouter’s full-catalogue popularity order. Sparse Vercel top-ten observations appear only when published and do not affect the score.

Arena preference

Status
Ranked
Source
LMArena
Official rank
#77 of 419
Rating
1452.3
95% confidence interval
1445–1460
Votes
6K
Source published at
28 Oct 2026, 00:00 UTC
Category
overall
Identity match confidence
100%

Market Gravity breakdown

Usage55%
35.8

OpenRouter weekly popularity across the full model catalogue.

Liquidity25%
91.9

Independent providers versus the model's open or closed cohort, weighted by uptime.

Open reach15%
96.4

Hugging Face 30-day downloads for open models; neutral for closed models.

Freshness5%
43.6

Time since first public availability, on a six-month half-life.

Specification

Model ID
google/gemma-4-31b-it
Context window
262K tokens
Declared output cap
16K tokens

OpenRouter catalogue or provider-endpoint declaration. Limits can vary by provider and prompt length; a model-wide maximum has not been independently verified. OpenRouter metadata

Inputs
Image, Text, Video
Outputs
Text
Tokenizer
Gemma
Cached input tokens
Not offered
First seen on OpenRouter
2 Apr 2026

Capabilities

  • Supported: Reasoning
  • Supported: Tool use
  • Supported: Structured output
  • Supported: Response format
  • Not supported: Moderated

Weights & access

Open weights. Downloadable weights are published under an OSI or free-culture license in the current repository metadata. This describes weight availability, not whether the full training stack qualifies as Open Source AI.

Access
Open weights
Licence
apache-2.0
Pinned revision
842da3794eaa
Parameters
31.3B
Architecture
Gemma4ForConditionalGeneration
Model type
gemma4
Hugging Face downloads (30d)
7.5M
Downloads (all time)
73.0M
Likes
4K
Repository updated
20 Jul 2026, 16:42 UTC
Base lineage
google/gemma-4-31B

Compare Gemma 4 31B with

Pick any model

Benchmark leaderboards featuring Gemma 4 31B

All leaderboards
Public benchmark boards on which Gemma 4 31B has a published result
LeaderboardScoreSource rankConfigurationPublished
Arena text leaderboardArena (LMArena)14521445–1460#77 of 419Not reported28 Oct 2026
Arena coding leaderboardArena (LMArena)15021487–1517#75 of 414Default28 Oct 2026
WildClawBench OpenClaw leaderboardWildClawBench37.6#25 of 34Default20 Jul 2026

Alternatives to Gemma 4 31B, by the numbers

Ranked neighbours

Models within 3 places of #37 on the ModelCap Index.

Cheaper at a similar or higher Index

Index score within 3 points of, or above, this model's, with a lower listed blended price (3:1 input:output).

Other ranked Google models

The same publisher's other current models with a public Index position.

Gemma 4 31B: common questions

How does Gemma 4 31B rank among AI models?

Gemma 4 31B holds ModelCap Index position #37 of 352 ranked language models as of 6 November 2026, with an Index score of 71.9 (interval 66.4–77.4); evidence: measured. The Index combines public benchmark boards with published uncertainty; the methodology page explains the weighting.

How much does Gemma 4 31B cost per 1M tokens?

Gemma 4 31B is listed at $0.20 per 1M input tokens and $0.40 per 1M output tokens as of 6 November 2026; the lowest output price among 16 providers is $0.10 on Modal. Prices come from the OpenRouter catalogue and re-observe on every refresh; at least one provider lists a free tier. For 1,000 requests using 2,000 input and 500 output tokens each, the listed rates imply $0.60 total (2M input + 0.5M output). This excludes caching, batch discounts, prompt-length tiers, tool charges and retries; verify the chosen endpoint's rate and limits before budgeting.

What is the context window of Gemma 4 31B?

Gemma 4 31B has a published context window of 262K tokens (262,144). The snapshot lists a 16,384 token catalogue-declared route output cap. OpenRouter catalogue or provider-endpoint declaration. Limits can vary by provider and prompt length; a model-wide maximum has not been independently verified. The providers table lists each endpoint's context limit.

Is Gemma 4 31B open-weight?

Open weights (apache-2.0). Downloadable weights are published under an OSI or free-culture license in the current repository metadata. This describes weight availability, not whether the full training stack qualifies as Open Source AI. The repository is google/gemma-4-31B-it on Hugging Face.

Which API providers serve Gemma 4 31B?

16 providers serve Gemma 4 31B through OpenRouter as of 6 November 2026: PrimeIntellect, CoreWeave, Venice, Chutes, DeepInfra and DekaLLM and 10 more. Each provider's price, context limit, quantization and measured uptime are in the providers table above.

Which benchmarks has Gemma 4 31B been evaluated on?

Gemma 4 31B has published results on 3 public boards tracked by ModelCap as of 6 November 2026: Arena text 1452 (#77 of 419), Arena coding 1502 (#75 of 414) and WildClawBench OpenClaw 37.6 (#25 of 34). Each board page ranks every tracked model on that benchmark. The ModelCap Index scores the results its methodology admits, with published uncertainty, and shows reference boards without scoring them.

How does Gemma 4 31B compare with Gemini 3.5 Flash Lite?

Gemma 4 31B ranks #37 (Index 71.9) and Gemini 3.5 Flash Lite ranks #34 (Index 72.8) on the ModelCap Index as of 6 November 2026. The head-to-head page lines up their benchmarks, listed prices, context windows and provider counts side by side.

When was Gemma 4 31B released?

Gemma 4 31B first appeared in the catalogue on 2 Apr 2026. It is the current version in its family. Rank and price movements since then are recorded on the site's changes feed.