Skip to main content
Radar

Provider changes are easy to miss. Radar watches releases, pricing, deprecations, and incidents at the source.Provider changes are easy to miss.

See Radar
BenchLM
Advertise

Model comparison

Qwen3.5-27B vs ZAYA1-74B-Preview

Updated August 7, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.

Qwen3.5-27B

Alibaba

59.6/100

Supported · Public rank #53

90% interval 50.8–68.5

ZAYA1-74B-Preview

Zyphra

—

Evidence status unavailable

90% interval unavailable

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

3 results are shared. Category rows based on different benchmark sets are marked directional and do not name a winner.

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

    Qwen3.5-27B

    Qwen3.5-27B 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

    The category averages use different weighted benchmark sets, so they are directional rather than like-for-like.

    Confidence: limited

  • Agentic work

    Tool use, computer use, and multi-step task completion

    Not enough matched evidence

    No shared weighted benchmark basis supports a winner.

    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

    A complete comparable API-rate estimate is not available for both models.

    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

What is actually comparable

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

Shared results
3
Qwen3.5-27B only
13
ZAYA1-74B-Preview only
4
Like-for-like categories
0 / 8

2 categories use different evidence sets. Those rows remain visible for coverage context but do not name a winner.

Category results, on a stated basis

Each row states whether both averages use the same weighted benchmark set. Directional and not-comparable rows remain visible, but they never receive a winner in this template.

Coding

Directional only
Qwen3.5-27B
64.9
ZAYA1-74B-Preview
53.2
Weighted basis
2 vs 1 rows
Reading
Directional only

Knowledge

Directional only
Qwen3.5-27B
82.7
ZAYA1-74B-Preview
66.1
Weighted basis
3 vs 2 rows
Reading
Directional only

Agentic

Not comparable
Qwen3.5-27B
52.0
ZAYA1-74B-Preview
Not measured
Weighted basis
3 vs 0 rows
Reading
Not comparable

Reasoning

Not comparable
Qwen3.5-27B
60.6
ZAYA1-74B-Preview
Not measured
Weighted basis
1 vs 0 rows
Reading
Not comparable

Math

Not comparable
Qwen3.5-27B
Not measured
ZAYA1-74B-Preview
76.4
Weighted basis
0 vs 1 rows
Reading
Not comparable

Multilingual

Not comparable
Qwen3.5-27B
82.2
ZAYA1-74B-Preview
Not measured
Weighted basis
1 vs 0 rows
Reading
Not comparable

Multimodal

Not comparable
Qwen3.5-27B
Not measured
ZAYA1-74B-Preview
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Instruction following

Not comparable
Qwen3.5-27B
95.0
ZAYA1-74B-Preview
Not measured
Weighted basis
1 vs 0 rows
Reading
Not comparable

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.

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

Qwen3.5-27B
Self-hosted; infrastructure cost varies
Fits in one request
ZAYA1-74B-Preview
Self-hosted; infrastructure cost varies
Fits in one request

Qwen3.5-27B has no comparable published API token rate. ZAYA1-74B-Preview has no comparable published API token rate.

Repository review

50K fresh input + 3K output tokens

Qwen3.5-27B
Self-hosted; infrastructure cost varies
Fits in one request
ZAYA1-74B-Preview
Self-hosted; infrastructure cost varies
Fits in one request

Qwen3.5-27B has no comparable published API token rate. ZAYA1-74B-Preview has no comparable published API token rate.

Cache-heavy agent loop

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

Qwen3.5-27B
Self-hosted; infrastructure cost varies
Fits in one request
Cached-input rate unavailable
ZAYA1-74B-Preview
Self-hosted; infrastructure cost varies
Fits in one request
Cached-input rate unavailable

Qwen3.5-27B has no comparable published API token rate. ZAYA1-74B-Preview 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.

Context window

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

Qwen3.5-27B

262K

ZAYA1-74B-Preview

256K

API model ID

Qwen3.5-27B

Not sourced

ZAYA1-74B-Preview

Not sourced

Cached-input rate

A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.

Qwen3.5-27B

No comparable hosted API rate

ZAYA1-74B-Preview

No comparable hosted API rate

Documented inputs

Qwen3.5-27B

Not sourced

ZAYA1-74B-Preview

Not sourced

Documented outputs

Qwen3.5-27B

Not sourced

ZAYA1-74B-Preview

Not sourced

Provider availability

Qwen3.5-27B

Not sourced

ZAYA1-74B-Preview

Not sourced

Reasoning profile

Qwen3.5-27B

Reasoning

ZAYA1-74B-Preview

Reasoning

Weight access

Qwen3.5-27B

Open Weight

ZAYA1-74B-Preview

Open Weight

License

Qwen3.5-27B

Open Weight

ZAYA1-74B-Preview

Open Weight

Release date

Qwen3.5-27B

2026-03-04

ZAYA1-74B-Preview

2026-05-07

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
Qwen3.5-27B has the larger documented window (262K).

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 evidence20 rows

Agentic

  • Terminal-Bench 2.0

    Qwen3.5-27B41.6%
    Source
    ZAYA1-74B-Preview—

    Not directly comparable

  • BrowseComp

    Qwen3.5-27B61%
    Source
    ZAYA1-74B-Preview—

    Not directly comparable

  • OSWorld-Verified

    Qwen3.5-27B56.2%
    Source
    ZAYA1-74B-Preview—

    Not directly comparable

  • Gert Labs

    Qwen3.5-27B39.41%
    Source
    ZAYA1-74B-Preview—

    Not directly comparable

  • τ²-bench Airline

    Qwen3.5-27B—
    ZAYA1-74B-Preview56.1%
    Source

    Not directly comparable

Coding

  • SWE-bench Verified

    Qwen3.5-27B72.4%
    Source
    ZAYA1-74B-Preview53.2%
    Source

    Qwen3.5-27B leads this result

  • SWE-Rebench

    Qwen3.5-27B58.9%
    Source
    ZAYA1-74B-Preview—

    Not directly comparable

  • LiveCodeBench v6

    Qwen3.5-27B—
    ZAYA1-74B-Preview65.7%
    Source

    Not directly comparable

Reasoning

  • LongBench v2

    Qwen3.5-27B60.6%
    Source
    ZAYA1-74B-Preview—

    Not directly comparable

Knowledge

  • MMLU-Pro

    Qwen3.5-27B86.1%
    Source
    ZAYA1-74B-Preview68.1%
    Source

    Qwen3.5-27B leads this result

  • SuperGPQA

    Qwen3.5-27B65.6%
    Source
    ZAYA1-74B-Preview—

    Not directly comparable

  • GPQA

    Qwen3.5-27B85.5%
    Source
    ZAYA1-74B-Preview57.3%
    Source

    Qwen3.5-27B leads this result

  • GPQA-D

    Qwen3.5-27B—
    ZAYA1-74B-Preview57.3%
    Source

    Not directly comparable

Math

  • AIME26

    Qwen3.5-27B—
    ZAYA1-74B-Preview76.4%
    Source

    Not directly comparable

Multilingual

  • MMLU-ProX

    Qwen3.5-27B82.2%
    Source
    ZAYA1-74B-Preview—

    Not directly comparable

Multimodal

  • MMMU

    Qwen3.5-27B82.3%
    Source
    ZAYA1-74B-Preview—

    Not directly comparable

  • MMVU

    Qwen3.5-27B73.3%
    Source
    ZAYA1-74B-Preview—

    Not directly comparable

  • MathVision

    Qwen3.5-27B86.0%
    Source
    ZAYA1-74B-Preview—

    Not directly comparable

  • V*

    Qwen3.5-27B93.7%
    Source
    ZAYA1-74B-Preview—

    Not directly comparable

Instruction following

  • IFEval

    Qwen3.5-27B95%
    Source
    ZAYA1-74B-Preview—

    Not directly comparable

Frequently asked questions

Which is better, Qwen3.5-27B or ZAYA1-74B-Preview?

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, Qwen3.5-27B or ZAYA1-74B-Preview?

The current coding averages use different weighted benchmark sets, so BenchLM does not name a winner from them. Read the shared benchmark rows directly and test the models on the same task set.

Which is better for agentic tasks, Qwen3.5-27B or ZAYA1-74B-Preview?

The published evidence does not provide a shared weighted agentic tasks basis for both models, so BenchLM does not name a agentic tasks winner.

Which costs less, Qwen3.5-27B or ZAYA1-74B-Preview?

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, Qwen3.5-27B or ZAYA1-74B-Preview?

Qwen3.5-27B has the larger documented context window: 262K, compared with 256K.

Related comparisons

Compare API pricing Read the methodology Open the model selector

Last updated August 7, 2026

Watch Qwen3.5-27B vs ZAYA1-74B-Preview

One weekly email when material rank, price, or benchmark evidence changes make this matchup worth revisiting.

Read a sample issue

Join 2,000+ readers.