Coding
Like-for-like- Mistral Medium 3.5 128B
- 77.6
- ZAYA1-74B-Preview
- 53.2
- Weighted basis
- 1 vs 1 rows
- Reading
- Mistral Medium 3.5 128B leads
Model comparison
Mistral Medium 3.5 128B 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.
1 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
Mistral Medium 3.5 128B
Mistral Medium 3.5 128B leads on the same 1 weighted benchmark row.
Confidence: limited
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
Long documents
Prompts that approach the documented context limit
No clear pick
The documented context windows are equal.
Confidence: documented
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: 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.
2 Mistral Medium 3.5 128B only
1 Shared
6 ZAYA1-74B-Preview only
- Shared results
- 1
- Mistral Medium 3.5 128B only
- 2
- ZAYA1-74B-Preview only
- 6
- Like-for-like categories
- 1 / 8
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.
Agentic
Not comparable- Mistral Medium 3.5 128B
- Not measured
- ZAYA1-74B-Preview
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
Reasoning
Not comparable- Mistral Medium 3.5 128B
- Not measured
- ZAYA1-74B-Preview
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
Knowledge
Not comparable- Mistral Medium 3.5 128B
- Not measured
- ZAYA1-74B-Preview
- 66.1
- Weighted basis
- 0 vs 2 rows
- Reading
- Not comparable
Math
Not comparable- Mistral Medium 3.5 128B
- Not measured
- ZAYA1-74B-Preview
- 76.4
- Weighted basis
- 0 vs 1 rows
- Reading
- Not comparable
Multilingual
Not comparable- Mistral Medium 3.5 128B
- Not measured
- ZAYA1-74B-Preview
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
Multimodal
Not comparable- Mistral Medium 3.5 128B
- Not measured
- ZAYA1-74B-Preview
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
Instruction following
Not comparable- Mistral Medium 3.5 128B
- Not measured
- ZAYA1-74B-Preview
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
| Category | Mistral Medium 3.5 128B | ZAYA1-74B-Preview | Weighted basis | Reading |
|---|---|---|---|---|
| Coding | 77.6 | 53.2 | Like-for-like1 vs 1 rows | Mistral Medium 3.5 128B leads |
| Agentic | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
| Reasoning | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
| Knowledge | Not measured | 66.1 | Not comparable0 vs 2 rows | Not comparable |
| Math | Not measured | 76.4 | Not comparable0 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.
SWE-bench Verified
Coding
Mistral Medium 3.5 128B: 77.6%ZAYA1-74B-Preview: 53.2%Normalized gap 24.4Mistral Medium 3.5 128B 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
- Mistral Medium 3.5 128B
- $0.00525
- 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
- Mistral Medium 3.5 128B
- $0.0975
- 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
- Mistral Medium 3.5 128B
- $0.405
- Fits 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
Mistral Medium 3.5 128B 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.
SpecificationMistral Medium 3.5 128BZAYA1-74B-Preview
Context window
Maximum documented context; output-token limits may be lower.
Mistral Medium 3.5 128B
256K
ZAYA1-74B-Preview
256K
API model ID
Mistral Medium 3.5 128B
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.
Mistral Medium 3.5 128B
Not published
ZAYA1-74B-Preview
No comparable hosted API rate
Documented inputs
Mistral Medium 3.5 128B
Not sourced
ZAYA1-74B-Preview
Not sourced
Documented outputs
Mistral Medium 3.5 128B
Not sourced
ZAYA1-74B-Preview
Not sourced
Provider availability
Mistral Medium 3.5 128B
Not sourced
ZAYA1-74B-Preview
Not sourced
Reasoning profile
Mistral Medium 3.5 128B
Reasoning
ZAYA1-74B-Preview
Reasoning
Weight access
Mistral Medium 3.5 128B
Open Weight
ZAYA1-74B-Preview
Open Weight
License
Mistral Medium 3.5 128B
Open Weight
ZAYA1-74B-Preview
Open Weight
Release date
Mistral Medium 3.5 128B
2026-04-29
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
- Both models list 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 evidence9 rows
Agentic
Coding
Knowledge
Math
AIME26
Mistral Medium 3.5 128B—ZAYA1-74B-Preview76.4%SourceNot directly comparable
Frequently asked questions
Which is better, Mistral Medium 3.5 128B 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, Mistral Medium 3.5 128B or ZAYA1-74B-Preview?
Mistral Medium 3.5 128B leads the like-for-like coding comparison across 1 shared weighted benchmark row.
Which is better for agentic tasks, Mistral Medium 3.5 128B 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, Mistral Medium 3.5 128B 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, Mistral Medium 3.5 128B or ZAYA1-74B-Preview?
Both models list the same context window, 256K.
Related comparisons
Last updated August 7, 2026
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