Coding
Like-for-like- Claude Sonnet 4.5
- 77.2
- ZAYA1-74B-Preview
- 53.2
- Weighted basis
- 1 vs 1 rows
- Reading
- Claude Sonnet 4.5 leads
Model comparison
Claude Sonnet 4.5 vs ZAYA1-74B-Preview
Updated August 7, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.
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 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.
Coding work
Code generation, repair, and software-engineering tasks
Claude Sonnet 4.5
Claude Sonnet 4.5 leads on the same 1 weighted benchmark row.
Confidence: limited
Long documents
Prompts that approach the documented context limit
ZAYA1-74B-Preview
ZAYA1-74B-Preview has the larger documented context window.
Confidence: documented
Show secondary and unsupported calls
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
The page does not recommend a cost winner because at least one model cannot fit the stated workload in one request. Claude Sonnet 4.5 does not fit this workload in one request. Claude Sonnet 4.5 has no published cached-input rate, so cached tokens use its listed input rate. ZAYA1-74B-Preview has no comparable published API token rate.
Confidence: rate-fallback
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.
9 Claude Sonnet 4.5 only
2 Shared
5 ZAYA1-74B-Preview only
- Shared results
- 2
- Claude Sonnet 4.5 only
- 9
- ZAYA1-74B-Preview only
- 5
- Like-for-like categories
- 1 / 8
1 category uses 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.
Knowledge
Directional only- Claude Sonnet 4.5
- 83.4
- ZAYA1-74B-Preview
- 66.1
- Weighted basis
- 1 vs 2 rows
- Reading
- Directional only
Agentic
Not comparable- Claude Sonnet 4.5
- 55.4
- ZAYA1-74B-Preview
- Not measured
- Weighted basis
- 2 vs 0 rows
- Reading
- Not comparable
Reasoning
Not comparable- Claude Sonnet 4.5
- 13.6
- ZAYA1-74B-Preview
- Not measured
- Weighted basis
- 1 vs 0 rows
- Reading
- Not comparable
Math
Not comparable- Claude Sonnet 4.5
- 11.2
- ZAYA1-74B-Preview
- 76.4
- Weighted basis
- 2 vs 1 rows
- Reading
- Not comparable
Multilingual
Not comparable- Claude Sonnet 4.5
- Not measured
- ZAYA1-74B-Preview
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
Multimodal
Not comparable- Claude Sonnet 4.5
- Not measured
- ZAYA1-74B-Preview
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
Instruction following
Not comparable- Claude Sonnet 4.5
- Not measured
- ZAYA1-74B-Preview
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
| Category | Claude Sonnet 4.5 | ZAYA1-74B-Preview | Weighted basis | Reading |
|---|---|---|---|---|
| Coding | 77.2 | 53.2 | Like-for-like1 vs 1 rows | Claude Sonnet 4.5 leads |
| Knowledge | 83.4 | 66.1 | Directional only1 vs 2 rows | Directional only |
| Agentic | 55.4 | Not measured | Not comparable2 vs 0 rows | Not comparable |
| Reasoning | 13.6 | Not measured | Not comparable1 vs 0 rows | Not comparable |
| Math | 11.2 | 76.4 | Not comparable2 vs 1 rows | Not comparable |
| Multilingual | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
| Multimodal | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
| Instruction following | Not measured | Not measured | Not comparable0 vs 0 rows | 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.
GPQA
Knowledge
Claude Sonnet 4.5: 83.4%ZAYA1-74B-Preview: 57.3%Normalized gap 26.1Claude Sonnet 4.5 source ZAYA1-74B-Preview sourceSWE-bench Verified
Coding
Claude Sonnet 4.5: 77.2%ZAYA1-74B-Preview: 53.2%Normalized gap 24.0Claude Sonnet 4.5 source ZAYA1-74B-Preview 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
- Claude Sonnet 4.5
- $0.0105
- Fits in one request
- ZAYA1-74B-Preview
- Self-hosted; infrastructure cost varies
- Fits in one request
ZAYA1-74B-Preview has no comparable published API token rate.
Repository review
50K fresh input + 3K output tokens
- Claude Sonnet 4.5
- $0.195
- Fits in one request
- ZAYA1-74B-Preview
- Self-hosted; infrastructure cost varies
- Fits in one request
ZAYA1-74B-Preview has no comparable published API token rate.
Cache-heavy agent loop
200K cached + 20K fresh input + 10K output tokens
- Claude Sonnet 4.5
- $0.81
- Does not fit in one request
- Cached input priced at the published list-input rate
- ZAYA1-74B-Preview
- Self-hosted; infrastructure cost varies
- Fits in one request
- Cached-input rate unavailable
Claude Sonnet 4.5 does not fit this workload in one request. Claude Sonnet 4.5 has no published cached-input rate, so cached tokens use its listed input 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.
SpecificationClaude Sonnet 4.5ZAYA1-74B-Preview
Context window
Maximum documented context; output-token limits may be lower.
Claude Sonnet 4.5
200K
ZAYA1-74B-Preview
256K
API model ID
Claude Sonnet 4.5
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.
Claude Sonnet 4.5
Not published
ZAYA1-74B-Preview
No comparable hosted API rate
Documented inputs
Claude Sonnet 4.5
Not sourced
ZAYA1-74B-Preview
Not sourced
Documented outputs
Claude Sonnet 4.5
Not sourced
ZAYA1-74B-Preview
Not sourced
Provider availability
Claude Sonnet 4.5
Not sourced
ZAYA1-74B-Preview
Not sourced
Reasoning profile
Claude Sonnet 4.5
Non-Reasoning
ZAYA1-74B-Preview
Reasoning
Weight access
Claude Sonnet 4.5
Proprietary
ZAYA1-74B-Preview
Open Weight
License
Claude Sonnet 4.5
Proprietary
ZAYA1-74B-Preview
Open Weight
Release date
Claude Sonnet 4.5
2025-09-01
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
- ZAYA1-74B-Preview has the larger documented window (256K).
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 evidence16 rows
Agentic
Terminal-Bench 2.0
Claude Sonnet 4.550%SourceZAYA1-74B-Preview—Not directly comparable
OSWorld-Verified
Claude Sonnet 4.561.4%SourceZAYA1-74B-Preview—Not directly comparable
VITA-Bench
Claude Sonnet 4.517.0%SourceZAYA1-74B-Preview—Not directly comparable
Gert Labs
Claude Sonnet 4.548.51%SourceZAYA1-74B-Preview—Not directly comparable
JobBench
Claude Sonnet 4.527.7%SourceZAYA1-74B-Preview—Not directly comparable
τ²-bench Airline
Claude Sonnet 4.5—ZAYA1-74B-Preview56.1%SourceNot directly comparable
Coding
Reasoning
ARC-AGI-2
Claude Sonnet 4.513.6%SourceZAYA1-74B-Preview—Not directly comparable
Knowledge
Math
AIME 2025
Claude Sonnet 4.587%SourceZAYA1-74B-Preview—Not directly comparable
FrontierMath v2 (Tiers 1-3)
Claude Sonnet 4.513.495%SourceZAYA1-74B-Preview—Not directly comparable
FrontierMath v2 (Tier 4)
Claude Sonnet 4.54.167%SourceZAYA1-74B-Preview—Not directly comparable
AIME26
Claude Sonnet 4.5—ZAYA1-74B-Preview76.4%SourceNot directly comparable
Frequently asked questions
Which is better, Claude Sonnet 4.5 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, Claude Sonnet 4.5 or ZAYA1-74B-Preview?
Claude Sonnet 4.5 leads the like-for-like coding comparison across 1 shared weighted benchmark row.
Which is better for agentic tasks, Claude Sonnet 4.5 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, Claude Sonnet 4.5 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, Claude Sonnet 4.5 or ZAYA1-74B-Preview?
ZAYA1-74B-Preview has the larger documented context window: 256K, compared with 200K.
Related comparisons
Last updated August 7, 2026
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