Knowledge
Like-for-like- Granite 4.2 8B
- 72.2
- ZAYA1-74B-Preview
- 66.1
- Weighted basis
- 2 vs 2 rows
- Reading
- Granite 4.2 8B leads
Five or fewer confirmed AI changes, with original sources, on mornings when something changed.A free source-linked morning brief.
See the free Radar BriefUpdated August 31, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.
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.
4 results are shared. Category rows based on different benchmark sets are marked directional and do not name a winner.
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.
Prompts that approach the documented context limit
ZAYA1-74B-Preview
ZAYA1-74B-Preview has the larger documented context window.
Confidence: documented
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
Tool use, computer use, and multi-step task completion
Not enough matched evidence
No shared weighted benchmark basis supports a winner.
Confidence: limited
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
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. Granite 4.2 8B does not fit this workload in one request. Granite 4.2 8B has no comparable published API token rate. ZAYA1-74B-Preview has no comparable published API token rate.
Confidence: listed-rates
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
Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.
1 category uses different evidence sets. Those rows remain visible for coverage context but do not name a winner.
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.
| Category | Granite 4.2 8B | ZAYA1-74B-Preview | Weighted basis | Reading |
|---|---|---|---|---|
| Knowledge | 72.2 | 66.1 | Like-for-like2 vs 2 rows | Granite 4.2 8B leads |
| Coding | 36.5 | 53.2 | Directional only3 vs 1 rows | Directional only |
| Agentic | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
| Reasoning | Not measured | Not measured | Not comparable0 vs 0 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 | 79.3 | Not measured | Not comparable1 vs 0 rows | Not comparable |
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
MMLU-Pro
Knowledge
SWE-bench Verified
Coding
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.
1K fresh input + 500 output tokens
Granite 4.2 8B has no comparable published API token rate. ZAYA1-74B-Preview has no comparable published API token rate.
50K fresh input + 3K output tokens
Granite 4.2 8B has no comparable published API token rate. ZAYA1-74B-Preview has no comparable published API token rate.
200K cached + 20K fresh input + 10K output tokens
Granite 4.2 8B does not fit this workload in one request. Granite 4.2 8B has no comparable published API token rate. ZAYA1-74B-Preview has no comparable published API token rate.
Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.
Maximum documented context; output-token limits may be lower.
Granite 4.2 8B
ZAYA1-74B-Preview
256K
Granite 4.2 8B
ibm-granite/granite-4.2-8b
IBM Granite 4.2 8B model cardZAYA1-74B-Preview
Not sourced
A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.
Granite 4.2 8B
No comparable hosted API rate
IBM Granite 4.2 8B model cardZAYA1-74B-Preview
No comparable hosted API rate
Granite 4.2 8B
Not sourced
ZAYA1-74B-Preview
Not sourced
Granite 4.2 8B
Not sourced
ZAYA1-74B-Preview
Not sourced
Granite 4.2 8B
Not sourced
ZAYA1-74B-Preview
Not sourced
Granite 4.2 8B
Reasoning
ZAYA1-74B-Preview
Reasoning
Granite 4.2 8B
Open Weight
ZAYA1-74B-Preview
Open Weight
Granite 4.2 8B
Open Weight
ZAYA1-74B-Preview
Open Weight
Granite 4.2 8B
2026-08-25
ZAYA1-74B-Preview
2026-05-07
Run the same representative tasks against both endpoints before changing production traffic.
The full public result ledger is available for audit without forcing a wide desktop table onto a phone.
Terminal-Bench 2.1
Not directly comparable
τ³-bench results
Not directly comparable
BFCL v4
Not directly comparable
τ²-bench Airline
Not directly comparable
SWE-bench Verified
ZAYA1-74B-Preview leads this result
SWE-bench Pro
Not directly comparable
SWE Multilingual
Not directly comparable
Terminal-Bench 2.1
Not directly comparable
LiveCodeBench v6
Granite 4.2 8B leads this result
SciCode
Not directly comparable
IFBench
Not directly comparable
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.
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.
The published evidence does not provide a shared weighted agentic tasks basis for both models, so BenchLM does not name a agentic tasks winner.
Both models do not have comparable published API token rates, so this page does not name a universal price winner.
ZAYA1-74B-Preview has the larger documented context window: 256K, compared with 128K.
Last updated August 31, 2026
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