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BenchLM

Data as of October 1, 2026 · How the score is built

EstablishedOpen WeightReasoning

Released Apr 2, 2026256K context

Gemma 4 26B A4B

Decision readingGemma 4 26B A4B scores 46.9 out of 100 and ranks #108 of 211. This profile shows 4 source-displayable benchmark rows; its strongest eligible category is Multimodal & Grounded at #42. Published weights can be self-hosted, but infrastructure cost varies and is not a comparable API token rate.

Released Apr 2, 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

46.9/100

field median 52.4#108 of 211 ranked models

Public

#108of 211

Verified #54 of 74

Price

Self-hosted; infrastructure cost varies

input median $1No comparable first-party hosted token rate

Speed

Not measured

field median 89 tok/sTime to first token not measured

Context

256Ktokens

field median 256,000Maximum output length is tracked separately

Strongest published evidence

Multimodal & Grounded ranks #42. Particularly strong for screenshots, documents, charts, and grounded multimodal workflows.

Validate before choosing

4 published rows leave some tracked benchmark slots empty. No comparable first-party API token rate is published.

Source-linked · 4 displayable benchmark rows

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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
AgenticWeight 22%0 benchmarksNot measured
Not measured
CodingWeight 20%0 benchmarksNot measured
Not measured
ReasoningWeight 17%0 benchmarksNot measured
Not measured
MultimodalRank #42 of 49Percentile 15thWeight 12%1 benchmarkVerified
45.2
KnowledgeRank #108 of 170Percentile 37thWeight 12%3 benchmarksVerified
36.5
MultilingualWeight 7%0 benchmarksNot measured
Not measured
Inst. FollowingWeight 5%0 benchmarksNot measured
Not measured
MathWeight 5%0 benchmarksNot measured
Not measured

4 of 508 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. AgenticNot measured
  2. CodingNot measured
  3. ReasoningNot measured
  4. Multimodal1/1 verified
  5. Knowledge3/3 verified
  6. MultilingualNot measured
  7. Inst. FollowingNot measured
  8. MathNot measured
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.

Gemma 4 26B A4B category percentile values

  • AgenticNot eligible
  • CodingNot eligible
  • ReasoningNot eligible
  • Multimodal15th percentile
  • Knowledge37th percentile
  • MultilingualNot eligible
  • Instruction followingNot eligible
  • MathNot eligible

The dashed outline is median of 6 nearest peers.

Eligible category ranks

  1. AgenticNot ranked
  2. CodingNot ranked
  3. ReasoningNot ranked
  4. Multimodal#42/49
  5. Knowledge#108/170
  6. MultilingualNot ranked
  7. Inst. FollowingNot ranked
  8. MathNot ranked
Top decileTop quartileMid-fieldNot eligible

Benchmark ledger

Multimodal 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.

Multimodal1 row
Multimodal benchmark values, best verified comparison, weight, and source status
MMMU-ProMassive Multi-discipline Multimodal Understanding ProScore73.8%Versus best verified row

Best verified: Gemini 3.5 Flash · 83.6%

Gap9.8 behindWeightWeighted 40%
Knowledge3 rows
Knowledge benchmark values, best verified comparison, weight, and source status
HLEHumanity's Last ExamScore17.2%Versus best verified row

Best verified: Claude Fable 5.1 · 65%

Gap47.8 behindWeight44% ref. weight
HLE w/o toolsHumanity's Last Exam without toolsScore8.7%Versus best verified row

Best verified: Claude Opus 5.5 · 64.4%

Gap55.7 behindWeight7% ref. weight
MMLU-ProMassive Multitask Language Understanding ProfessionalScore82.6%Versus best verified row

Best verified: Qwen3.7 Max · 89.6%

Gap7 behindWeight6% ref. weight

Bars run 0–100; the dark tick marks the best source-verified value

All 4 rows

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.

Radar

Gemma 4 26B A4B release history

Full release history

Radar confirmed these at the source. Use Gemma 4 26B A4B in your work? Explore Radar to follow supported changes and choose your alerts.

Radar

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
gemma-4-26b-a4b-itGoogle Gemma Gemini API guide
Maximum output
Not sourced yet
Knowledge cutoff
Not sourced yet
Input modalities
text, imageGoogle Gemma 4 model documentation
Parameters
Not sourced yet
Availability
Gemini API · Google AI Studio · open weightsGoogle Gemma Gemini API guide
Cloud regions
Not tracked yet
API capabilities
Tool calling, structured outputs, and batch support are not tracked yet
Prompt caching
Not documented in the pricing record
Self-host
Open weights available; hardware estimate not sourced
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.

Gemma 4 26B A4B ranks #108 of 211 on the public leaderboard with a score of 46.88/100. Its source-verified position is #54 of 74.

Gemma 4 26B A4B is a open weight model with a 256K context window. It uses an explicit reasoning mode, which can improve complex problem solving while adding latency and token use.

Official exact-value snapshot from Google's April 2, 2026 Gemma 4 model card and launch post. BenchLM maps only schema-equivalent results from the published table: MMLU Pro, GPQA Diamond, LiveCodeBench v6, HLE no tools / with search, BigBench Extra Hard, MMMU Pro, and MRCR v2. AIME 2026, Codeforces, MMMLU, OmniDocBench 1.5, MATH-Vision, MedXPertQA MM, audio benchmarks, and Tau2 (average over 3) remain out-of-schema or non-equivalent to current weighted keys.

Gemma 4 26B A4B sits in the Gemma 4 family with Gemma 4 31B, Gemma 4 12B, Gemma 4 E4B, Gemma 4 E2B. 4 of 508 tracked benchmark slots currently have displayable evidence. Missing categories stay blank.

Its strongest eligible category is Multimodal & Grounded at #42, while its lowest eligible position is Knowledge at #108. particularly strong for screenshots, documents, charts, and grounded multimodal workflows.

Last updated October 1, 2026. Runtime fields remain blank until a sourced snapshot exists.

Deployment options

Self-host and provider-specific paths stay separate from benchmark evidence so operating constraints are visible before a score becomes the whole decision.

Published weights are available, but BenchLM does not yet have a sourced parameter and VRAM profile for this exact model. Hardware cost estimates stay unavailable until that sizing record is complete.

Estimate VRAM from known parameters

Questions

How does Gemma 4 26B A4B perform overall in AI benchmarks?

Gemma 4 26B A4B ranks #108 out of 211 models on the public BenchAlign leaderboard, with a score of 46.88/100. Its evidence status is Supported, and this profile shows 4 source-displayable benchmark rows. The label describes evidence depth, not a provider quality claim; inspect category rows before choosing a workload.

Is Gemma 4 26B A4B good for knowledge and understanding?

Gemma 4 26B A4B ranks #108 out of 170 eligible models for knowledge and understanding, with a public category score of 36.5/100. 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 Gemma 4 26B A4B good for multimodal and grounded tasks?

Gemma 4 26B A4B ranks #42 out of 49 eligible models for multimodal and grounded tasks, with a public category score of 45.2/100. 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 Gemma 4 26B A4B open source?

Gemma 4 26B A4B is an open-weight model from Google. Its weights can be downloaded for local or hosted deployment, subject to the published license. Open weight does not automatically mean open source: training data and training code may remain private, and commercial restrictions can still apply.

Which sibling models are related to Gemma 4 26B A4B?

Gemma 4 26B A4B belongs to the Gemma 4 family. Related tracked variants include Gemma 4 31B, Gemma 4 12B, Gemma 4 E4B, plus 1 more. A sibling link indicates shared lineage or a documented configuration relationship; it does not mean the variants have identical pricing, context limits, benchmark evidence, or deployment behavior. Compare before switching.

Does Gemma 4 26B A4B have full benchmark coverage on BenchLM?

No. Gemma 4 26B A4B currently has 19 source-displayable rows across 508 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 Gemma 4 26B A4B?

Gemma 4 26B A4B has a documented context window of 256K. 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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