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ModelCap

Gemma 4 26B A4B

Arena #101Official publisher releaseOpen weightsFree tier7d #55 → #56

Google·#56 of 352 on the current board·cheaper than #55 Muse Glimmer 30B

Gemma 4 26B A4B is a language model from Google. It ranks #56 of 352 on ModelCap's current board, with an Index score of 66.8, measured on 2 public benchmarks. Its score range of 61.3–72.3 spans positions #36–#79. It is listed at $0.09 per million input tokens and $0.30 per million output tokens across 15 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
66.8#56
Measured on 2 public benchmarks · range 61.3–72.3
Evidence as of 28 Oct 2026, 00:00 UTC
Market Gravity
56.4Increased by 0.6
Secondary market signal
Input
$0.09
per 1M tokens
Output
$0.30
per 1M tokens
Context
262K
tokens
Providers
15
endpoints

Providers

Uptime measured over the last 30 minutes
ProviderInputOutputContextQuantUptime
MakoraCheapest$0.08$0.10256K—100.0%
PrimeIntellectbf16$0.034$0.103262Kbf1696.67%
Darkbloom$0.04$0.15131K—100.0%
AkashMLfp4$0.07$0.24131Kfp4100.0%
Cloudflare$0.10$0.30256K—100.0%
CoreWeavebf16$0.10$0.30262Kbf1686.67%
NextBitbf16$0.09$0.30262Kbf16100.0%
Io Netbf16$0.09$0.31262Kbf16100.0%
DekaLLMbf16$0.06$0.33262Kbf16100.0%
DeepInfrafp8$0.07$0.34262Kfp8100.0%
Novitabf16$0.13$0.40262Kbf16100.0%
Parasailbf16$0.13$0.40262Kbf16100.0%
SiliconFlowfp8$0.14$0.40262Kfp8100.0%
Venicebf16$0.13$0.40256Kbf16100.0%
Googleglobal$0.15$0.60262K—100.0%

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
$0.07$0.34262K223 ms59.9 tok/stools · structured
novita
live
$0.13$0.40262K536 ms66.5 tok/stools · structured
featherless-ai
live
——————

Reported evaluation leads (21)

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
allenai/IFBench_test
prompt_level_loose
—72
Unpinned
not published
Reported
Quarantined
cais/hle
hle
—17.2
Unpinned
not published
Reported
Quarantined
google/physical-engineerings-last-exam
overall-score
—5.2
Unpinned
not published
Reported
Quarantined
Idavidrein/gpqa
diamond
—82.3
Unpinned
not published
Reported
Quarantined
llamaindex/ExtractBench
mean
—70.27
Unpinned
not published
Reported
Quarantined
llamaindex/ExtractBench
short
—77.7
Unpinned
not published
Reported
Quarantined
llamaindex/ExtractBench
medium
—59.61
Unpinned
not published
Reported
Quarantined
llamaindex/ExtractBench
long
—28.88
Unpinned
not published
Reported
Quarantined
llamaindex/ParseBench
mean
—58.5
Unpinned
not published
Reported
Quarantined
llamaindex/ParseBench
text_content
—83.8
Unpinned
not published
Reported
Quarantined
llamaindex/ParseBench
text_formatting
—65.1
Unpinned
not published
Reported
Quarantined
llamaindex/ParseBench
layout
—59.2
Unpinned
not published
Reported
Quarantined
llamaindex/ParseBench
chart
—14.2
Unpinned
not published
Reported
Quarantined
llamaindex/ParseBench
table
—70
Unpinned
not published
Reported
Quarantined
MBZUAI/longshot-bench
overall
—34.76
Unpinned
not published
Reported
Quarantined
MBZUAI/longshot-bench
core_perception
—29.78
Unpinned
not published
Reported
Quarantined
MBZUAI/longshot-bench
reasoning
—40.44
Unpinned
not published
Reported
Quarantined
MBZUAI/longshot-bench
information
—33.13
Unpinned
not published
Reported
Quarantined
MBZUAI/longshot-bench
multimodal
—35.68
Unpinned
not published
Reported
Quarantined
MMMU/MMMU_Pro
mmmu_pro_vision
—73.8
Unpinned
not published
Reported
Quarantined

Showing 20 of 21 rows.

Other versions (1)

ModelCap Index · Current board

Methodology
66.8
Measured on 2 public benchmarks
Current board
#56 of 352
Score range
61.3–72.3
Rank range
#36–#79
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
56.2% · strong
Identity binding
Exact catalogue product · google/google/gemma-4-26b-a4b-it · aggregates disclosed benchmark configurations · endpoint configuration not claimed · artifact metadata google/gemma-4-26B-A4B-it@4d7ae4984b7db7de8f8457170b3f1a419ee76d52 (not the evaluation revision)
Index observations used
2
Qualified Index evidence point
66.8
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
66.8
Evidence status
confirmed · 75% mass
General preference
67.0
Coding
65.3
Agents & tools
—
Reasoning
—
Evidence breadth
92%
Evidence coverage
56%
Market and catalogue signals · secondary, never the language Index rank
Usage (OpenRouter popularity)
33.9
Liquidity (providers × uptime)
90.3
Open reach (HF downloads)
86.4
Surface (context / tools / modalities)
90.3
Freshness
43.8
  • · OpenRouter popularity #47
  • · 15 live providers
  • · HF 30d downloads 5661805
  • · Catalogue: context 262144, reasoning, tools, modalities Image/Text/Video
  • · First seen 2026-04-03

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
98.9
Evaluation provenance
50.1

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
56.4
OpenRouter weekly popularity
#47 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
#101 of 419
Rating
1437.6
95% confidence interval
1430–1445
Votes
6K
Source published at
28 Oct 2026, 00:00 UTC
Category
overall
Identity match confidence
100%

Market Gravity breakdown

Usage55%
33.9

OpenRouter weekly popularity across the full model catalogue.

Liquidity25%
90.3

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

Open reach15%
86.4

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

Freshness5%
43.8

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

Specification

Model ID
google/gemma-4-26b-a4b-it
Context window
262K tokens
Declared output cap
236K 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
$0.05 / 1M
First seen on OpenRouter
3 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
4d7ae4984b7d
Parameters
25.8B
Architecture
Gemma4ForConditionalGeneration
Model type
gemma4
Hugging Face downloads (30d)
5.7M
Downloads (all time)
75.1M
Likes
2K
Repository updated
20 Jul 2026, 16:42 UTC

Compare Gemma 4 26B A4B with

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Benchmark leaderboards featuring Gemma 4 26B A4B

All leaderboards
Public benchmark boards on which Gemma 4 26B A4B has a published result
LeaderboardScoreSource rankConfigurationPublished
Arena text leaderboardArena (LMArena)14381430–1445#101 of 419Not reported28 Oct 2026
Arena coding leaderboardArena (LMArena)14821468–1497#109 of 414Default28 Oct 2026

Alternatives to Gemma 4 26B A4B, by the numbers

Ranked neighbours

Models within 3 places of #56 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 26B A4B: common questions

How does Gemma 4 26B A4B rank among AI models?

Gemma 4 26B A4B holds ModelCap Index position #56 of 352 ranked language models as of 6 November 2026, with an Index score of 66.8 (interval 61.3–72.3); evidence: measured. The Index combines public benchmark boards with published uncertainty; the methodology page explains the weighting.

How much does Gemma 4 26B A4B cost per 1M tokens?

Gemma 4 26B A4B is listed at $0.09 per 1M input tokens and $0.30 per 1M output tokens as of 6 November 2026; the lowest output price among 15 providers is $0.10 on Makora. 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 $0.33 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 26B A4B?

Gemma 4 26B A4B has a published context window of 262K tokens (262,144). The snapshot lists a 235,929 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 26B A4B 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-4-26B-A4B-it on Hugging Face.

Which API providers serve Gemma 4 26B A4B?

15 providers serve Gemma 4 26B A4B through OpenRouter as of 6 November 2026: PrimeIntellect, Darkbloom, DekaLLM, AkashML, DeepInfra and Makora and 9 more. Each provider's price, context limit, quantization and measured uptime are in the providers table above.

Which benchmarks has Gemma 4 26B A4B been evaluated on?

Gemma 4 26B A4B has published results on 2 public boards tracked by ModelCap as of 6 November 2026: Arena text 1438 (#101 of 419) and Arena coding 1482 (#109 of 414). 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 26B A4B compare with Gemma 4 31B?

Gemma 4 26B A4B ranks #56 (Index 66.8) and Gemma 4 31B ranks #37 (Index 71.9) 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 26B A4B released?

Gemma 4 26B A4B first appeared in the catalogue on 3 Apr 2026. It is the current version in its family. Rank and price movements since then are recorded on the site's changes feed.