Gemma 4 E2B vs ZAYA1-8B

Decision reading

At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner.

2 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.

Model A

Gemma 4 E2B

Google

39.58/100

Estimated · Public rank #192

90% interval 28.1–51.1

Model B

ZAYA1-8B

Zyphra

—

Evidence status unavailable

90% interval unavailable

Updated September 18, 2026. We do not rank this pair: at least one has no public score. Public scores include evidence status and uncertainty.

Share or export

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
ZAYA1-8B
ZAYA1-8B has the larger documented context window.
Confidence: documented

Show secondary and unsupported calls

Coding work
Code generation, repair, and software-engineering tasks
Not enough matched evidence
ZAYA1-8B is not ranked on the public lane for coding, so no winner is named for coding.
Confidence: limited
Agentic work
Tool use, computer use, and multi-step task completion
Not enough matched evidence
Gemma 4 E2B and ZAYA1-8B are scored on Estimated evidence for agentic, so the reading is directional rather than like-for-like.
Confidence: limited
Chat turn cost
1K fresh input + 500 output tokens
Not enough matched evidence
A complete comparable API-rate estimate is not available for both models.
Confidence: listed-rates
Cache-heavy agent loop cost
200K cached + 20K fresh input + 10K output tokens
Not enough matched evidence
The page does not recommend a cost winner because at least one model cannot fit the stated workload in one request. Gemma 4 E2B does not fit this workload in one request. ZAYA1-8B does not fit this workload in one request. Gemma 4 E2B has no comparable published API token rate. ZAYA1-8B has no comparable published API token rate.
Confidence: listed-rates
Repository review cost
50K fresh input + 3K output tokens
Not enough matched evidence
A complete comparable API-rate estimate is not available for both models.
Confidence: listed-rates

Which one for a specific job

Choose a job from the LLM Selector's task catalog to see the category row it rests on, under the same basis rules as the table below. A directional row stays directional; choosing a job never creates a winner.

Pick the job you would use them for

The same task catalog as the LLM Selector. Each job names the evidence surface it rests on; nothing here adds a new score.

39.0Gemma 4 E2B—ZAYA1-8B

Not comparable · BenchAlign

The coding row is not comparable on the public lane: at least one model is not measured or not ranked there.

Coding scores combine specific tasks and setups. Match the editor, harness, and effort to your workflow.

Open the coding leaderboard Shortlist models for this job

What is actually comparable

Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.

2 Shared

9 ZAYA1-8B only

Shared results: 2
Gemma 4 E2B only: 0
ZAYA1-8B only: 9
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

Gemma 4 E2B: 43.3; Estimated · #101/154
ZAYA1-8B: 46.1; Estimated · #82/154
Basis: BenchAlign lane · 0 vs 1 public rows
Reading: Directional only

Knowledge

Directional only

Gemma 4 E2B: 36.6; Estimated · #153/184
ZAYA1-8B: 43.6; Estimated · #120/184
Basis: BenchAlign lane · 2 vs 3 public rows
Reading: Directional only

Instruction following

Directional only

Gemma 4 E2B: 42.4; #96/124
ZAYA1-8B: 23.5; #121/124
Basis: Provisional lane · 0 vs 1 weighted rows
Reading: Directional only

Coding

Not comparable

Gemma 4 E2B: 39.0; Estimated · #126/154
ZAYA1-8B: Not ranked
Basis: BenchAlign lane · 0 vs 1 public rows
Reading: Not comparable

Reasoning

Not comparable

Gemma 4 E2B: 32.2; Unranked · 2 rankable rows
ZAYA1-8B: Not ranked
Basis: Provisional lane · 0 vs 0 weighted rows
Reading: Not comparable

Math

Not comparable

Gemma 4 E2B: Not ranked
ZAYA1-8B: 61.3; Unranked · 4 rankable rows
Basis: Provisional lane · 0 vs 2 weighted rows
Reading: Not comparable

Multilingual

Not comparable

Gemma 4 E2B: Not ranked
ZAYA1-8B: Not ranked
Basis: Provisional lane · 0 vs 0 weighted rows
Reading: Not comparable

Multimodal

Not comparable

Gemma 4 E2B: 25.8; Unranked · 1 rankable row
ZAYA1-8B: Not ranked
Basis: Provisional lane · 0 vs 0 weighted rows
Reading: Not comparable

Category scores with the server-provided evidence basis for Gemma 4 E2B and ZAYA1-8B
Category	Gemma 4 E2B	ZAYA1-8B	Basis	Reading
Agentic	43.3Estimated · #101/154	46.1Estimated · #82/154	Directional onlyBenchAlign lane · 0 vs 1 public rows	Directional only
Knowledge	36.6Estimated · #153/184	43.6Estimated · #120/184	Directional onlyBenchAlign lane · 2 vs 3 public rows	Directional only
Instruction following	42.4#96/124	23.5#121/124	Directional onlyProvisional lane · 0 vs 1 weighted rows	Directional only
Coding	39.0Estimated · #126/154	Not ranked	Not comparableBenchAlign lane · 0 vs 1 public rows	Not comparable
Reasoning	32.2Unranked · 2 rankable rows	Not ranked	Not comparableProvisional lane · 0 vs 0 weighted rows	Not comparable
Math	Not ranked	61.3Unranked · 4 rankable rows	Not comparableProvisional lane · 0 vs 2 weighted rows	Not comparable
Multilingual	Not ranked	Not ranked	Not comparableProvisional lane · 0 vs 0 weighted rows	Not comparable
Multimodal	25.8Unranked · 1 rankable row	Not ranked	Not comparableProvisional lane · 0 vs 0 weighted rows	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.

GPQA
Knowledge
Gemma 4 E2B: 43.4%ZAYA1-8B: 71%Normalized gap 27.6Gemma 4 E2B source ZAYA1-8B source
MMLU-Pro
Knowledge
Gemma 4 E2B: 60%ZAYA1-8B: 74.2%Normalized gap 14.2Gemma 4 E2B source ZAYA1-8B source

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

Gemma 4 E2B: Self-hosted; infrastructure cost varies; Fits in one request
ZAYA1-8B: Self-hosted; infrastructure cost varies; Fits in one request

Gemma 4 E2B has no comparable published API token rate. ZAYA1-8B has no comparable published API token rate.

Repository review

50K fresh input + 3K output tokens

Gemma 4 E2B: Self-hosted; infrastructure cost varies; Fits in one request
ZAYA1-8B: Self-hosted; infrastructure cost varies; Fits in one request

Gemma 4 E2B has no comparable published API token rate. ZAYA1-8B has no comparable published API token rate.

Cache-heavy agent loop

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

Gemma 4 E2B: Self-hosted; infrastructure cost varies; Does not fit in one request; Cached-input rate unavailable
ZAYA1-8B: Self-hosted; infrastructure cost varies; Does not fit in one request; Cached-input rate unavailable

Gemma 4 E2B does not fit this workload in one request. ZAYA1-8B does not fit this workload in one request. Gemma 4 E2B has no comparable published API token rate. ZAYA1-8B has no comparable published API token rate.

Specification differences

Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.

SpecificationGemma 4 E2BZAYA1-8B

Context window

Maximum documented context; output-token limits may be lower.

Gemma 4 E2B

128K

Google Gemma 4 model documentation

ZAYA1-8B

131K

Gemma 4 E2B

Reasoning

ZAYA1-8B

Reasoning

Weight access

Gemma 4 E2B

Open Weight

ZAYA1-8B

Open Weight

License

Gemma 4 E2B

Open Weight

ZAYA1-8B

Open Weight

Release date

Gemma 4 E2B

2026-04-02

ZAYA1-8B

2026-05-05

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: At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner.
Workload cost: A complete comparable API-rate estimate is not available for both models.
Context tradeoff: ZAYA1-8B has the larger documented window (131K).

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 evidence11 rows

Agentic

BFCL v4
Gemma 4 E2B—
ZAYA1-8B39.2%
Source
Not directly comparable

Coding

LiveCodeBench v6
Gemma 4 E2B—
ZAYA1-8B65.8%
Source
Not directly comparable

Knowledge

GPQA
Gemma 4 E2B43.4%
Source
ZAYA1-8B71%
Source
ZAYA1-8B leads this result
MMLU-Pro
Gemma 4 E2B60%
Source
ZAYA1-8B74.2%
Source
ZAYA1-8B leads this result
GPQA-D
Gemma 4 E2B—
ZAYA1-8B71.0%
Source
Not directly comparable

Math

AIME26
Gemma 4 E2B—
ZAYA1-8B89.1%
Source
Not directly comparable
HMMT Feb 2026
Gemma 4 E2B—
ZAYA1-8B71.6%
Source
Not directly comparable
IMOAnswerBench
Gemma 4 E2B—
ZAYA1-8B59.3%
Source
Not directly comparable
Apex
Gemma 4 E2B—
ZAYA1-8B32.2%
Source
Not directly comparable

Instruction following

IFEval
Gemma 4 E2B—
ZAYA1-8B85.6%
Source
Not directly comparable
IFBench
Gemma 4 E2B—
ZAYA1-8B52.6%
Source
Not directly comparable

Questions

Which is better, Gemma 4 E2B or ZAYA1-8B?

At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner. The page therefore keeps the decision tied to the specific documented workload.

Which is better for coding, Gemma 4 E2B or ZAYA1-8B?

ZAYA1-8B is not ranked on the public lane for coding, so no winner is named for coding.

Which is better for agentic tasks, Gemma 4 E2B or ZAYA1-8B?

ZAYA1-8B scores higher for agentic tasks on the public lane, 46.1 to 43.3. Gemma 4 E2B and ZAYA1-8B 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, Gemma 4 E2B or ZAYA1-8B?

Both models do not have comparable published API token rates, so this page does not name a universal price winner.

Which has the larger context window, Gemma 4 E2B or ZAYA1-8B?

ZAYA1-8B has the larger documented context window: 131K, compared with 128K.

Related comparisons

Compare API pricing Read the methodology Open the model selector

Last updated September 18, 2026

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Gemma 4 E2B vs ZAYA1-8B

Which one for your work

Long documents

Coding work

Agentic work

Chat turn cost

Cache-heavy agent loop cost

Repository review cost

Which one for a specific job

What is actually comparable

Category results, on a stated basis

Agentic

Knowledge

Instruction following

Coding

Reasoning

Math

Multilingual

Multimodal

Shape of the matched evidence

What each workload costs

Chat turn

Repository review

Cache-heavy agent loop

Specification differences

Context window

API model ID

Cached-input rate

Documented inputs

Documented outputs

Provider availability

Reasoning profile

Weight access

License

Release date

Benchmark evidence

Agentic

Coding

Knowledge

Math

Instruction following

Questions

Which is better, Gemma 4 E2B or ZAYA1-8B?

Which is better for coding, Gemma 4 E2B or ZAYA1-8B?

Which is better for agentic tasks, Gemma 4 E2B or ZAYA1-8B?

Which costs less, Gemma 4 E2B or ZAYA1-8B?

Which has the larger context window, Gemma 4 E2B or ZAYA1-8B?

Related comparisons

Watch Gemma 4 E2B vs ZAYA1-8B