Knowledge
Like-for-like- Kimi K2.5 (Reasoning)
- 87.2
- ZAYA1-8B
- 73.6
- Weighted basis
- 2 vs 2 rows
- Reading
- Kimi K2.5 (Reasoning) leads
Model comparison
Kimi K2.5 (Reasoning) vs ZAYA1-8B
Updated August 5, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.
Kimi K2.5 (Reasoning) has the higher public score, 58.47 versus 31.58, and the 90% score intervals do not overlap.
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.
Long documents
Prompts that approach the documented context limit
Kimi K2.5 (Reasoning)
Kimi K2.5 (Reasoning) 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
No shared weighted benchmark basis supports a winner.
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
The page does not recommend a cost winner because at least one model cannot fit the stated workload in one request. ZAYA1-8B does not fit this workload in one request. Kimi K2.5 (Reasoning) has no published cached-input rate, so cached tokens use its listed input rate. ZAYA1-8B 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.
7 Kimi K2.5 (Reasoning) only
2 Shared
9 ZAYA1-8B only
- Shared results
- 2
- Kimi K2.5 (Reasoning) only
- 7
- ZAYA1-8B only
- 9
- 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- Kimi K2.5 (Reasoning)
- 55.0
- ZAYA1-8B
- Not measured
- Weighted basis
- 2 vs 0 rows
- Reading
- Not comparable
Coding
Not comparable- Kimi K2.5 (Reasoning)
- 76.8
- ZAYA1-8B
- Not measured
- Weighted basis
- 1 vs 0 rows
- Reading
- Not comparable
Reasoning
Not comparable- Kimi K2.5 (Reasoning)
- Not measured
- ZAYA1-8B
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
Math
Not comparable- Kimi K2.5 (Reasoning)
- Not measured
- ZAYA1-8B
- 80.4
- Weighted basis
- 0 vs 2 rows
- Reading
- Not comparable
Multilingual
Not comparable- Kimi K2.5 (Reasoning)
- Not measured
- ZAYA1-8B
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
Multimodal
Not comparable- Kimi K2.5 (Reasoning)
- 78.5
- ZAYA1-8B
- Not measured
- Weighted basis
- 1 vs 0 rows
- Reading
- Not comparable
Instruction following
Not comparable- Kimi K2.5 (Reasoning)
- Not measured
- ZAYA1-8B
- 64.1
- Weighted basis
- 0 vs 2 rows
- Reading
- Not comparable
| Category | Kimi K2.5 (Reasoning) | ZAYA1-8B | Weighted basis | Reading |
|---|---|---|---|---|
| Knowledge | 87.2 | 73.6 | Like-for-like2 vs 2 rows | Kimi K2.5 (Reasoning) leads |
| Agentic | 55.0 | Not measured | Not comparable2 vs 0 rows | Not comparable |
| Coding | 76.8 | Not measured | Not comparable1 vs 0 rows | Not comparable |
| Reasoning | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
| Math | Not measured | 80.4 | Not comparable0 vs 2 rows | Not comparable |
| Multilingual | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
| Multimodal | 78.5 | Not measured | Not comparable1 vs 0 rows | Not comparable |
| Instruction following | Not measured | 64.1 | Not comparable0 vs 2 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
Kimi K2.5 (Reasoning): 87.6%ZAYA1-8B: 71%Normalized gap 16.6Kimi K2.5 (Reasoning) source ZAYA1-8B sourceMMLU-Pro
Knowledge
Kimi K2.5 (Reasoning): 87.1%ZAYA1-8B: 74.2%Normalized gap 12.9Kimi K2.5 (Reasoning) 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
- Kimi K2.5 (Reasoning)
- $0.0021
- Fits in one request
- ZAYA1-8B
- Self-hosted; infrastructure cost varies
- Fits in one request
ZAYA1-8B has no comparable published API token rate.
Repository review
50K fresh input + 3K output tokens
- Kimi K2.5 (Reasoning)
- $0.039
- Fits in one request
- ZAYA1-8B
- Self-hosted; infrastructure cost varies
- Fits in one request
ZAYA1-8B has no comparable published API token rate.
Cache-heavy agent loop
200K cached + 20K fresh input + 10K output tokens
- Kimi K2.5 (Reasoning)
- $0.162
- Fits in one request
- Cached input priced at the published list-input rate
- ZAYA1-8B
- Self-hosted; infrastructure cost varies
- Does not fit in one request
- Cached-input rate unavailable
ZAYA1-8B does not fit this workload in one request. Kimi K2.5 (Reasoning) has no published cached-input rate, so cached tokens use its listed input 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.
SpecificationKimi K2.5 (Reasoning)ZAYA1-8B
Context window
Maximum documented context; output-token limits may be lower.
Kimi K2.5 (Reasoning)
256K
ZAYA1-8B
131K
API model ID
Kimi K2.5 (Reasoning)
Not sourced
ZAYA1-8B
Not sourced
Cached-input rate
A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.
Kimi K2.5 (Reasoning)
Not published
ZAYA1-8B
No comparable hosted API rate
Documented inputs
Kimi K2.5 (Reasoning)
Not sourced
ZAYA1-8B
Not sourced
Documented outputs
Kimi K2.5 (Reasoning)
Not sourced
ZAYA1-8B
Not sourced
Provider availability
Kimi K2.5 (Reasoning)
Not sourced
ZAYA1-8B
Not sourced
Reasoning profile
Kimi K2.5 (Reasoning)
Reasoning
ZAYA1-8B
Reasoning
Weight access
Kimi K2.5 (Reasoning)
Proprietary
ZAYA1-8B
Open Weight
License
Kimi K2.5 (Reasoning)
Proprietary
ZAYA1-8B
Open Weight
Release date
Kimi K2.5 (Reasoning)
2026-02-01
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
- Kimi K2.5 (Reasoning) has the higher public score, 58.47 versus 31.58, and the 90% score intervals do not overlap.
- Workload cost
- A complete comparable API-rate estimate is not available for both models.
- Context tradeoff
- Kimi K2.5 (Reasoning) 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 evidence18 rows
Agentic
Terminal-Bench 2.0
Kimi K2.5 (Reasoning)50.8%SourceZAYA1-8B—Not directly comparable
BrowseComp
Kimi K2.5 (Reasoning)60.6%SourceZAYA1-8B—Not directly comparable
Gert Labs
Kimi K2.5 (Reasoning)32.58%SourceZAYA1-8B—Not directly comparable
BFCL v4
Kimi K2.5 (Reasoning)—ZAYA1-8B39.2%SourceNot directly comparable
Coding
Knowledge
Math
AIME 2025
Kimi K2.5 (Reasoning)96.1%SourceZAYA1-8B—Not directly comparable
AIME26
Kimi K2.5 (Reasoning)—ZAYA1-8B89.1%SourceNot directly comparable
HMMT Feb 2026
Kimi K2.5 (Reasoning)—ZAYA1-8B71.6%SourceNot directly comparable
IMOAnswerBench
Kimi K2.5 (Reasoning)—ZAYA1-8B59.3%SourceNot directly comparable
Apex
Kimi K2.5 (Reasoning)—ZAYA1-8B32.2%SourceNot directly comparable
Multimodal
MMMU-Pro
Kimi K2.5 (Reasoning)78.5%SourceZAYA1-8B—Not directly comparable
Instruction following
Frequently asked questions
Which is better, Kimi K2.5 (Reasoning) or ZAYA1-8B?
Kimi K2.5 (Reasoning) has the higher public score, 58.47 versus 31.58, and the 90% score intervals do not overlap. That is the clearest overall quality signal in the current public data.
Which is better for coding, Kimi K2.5 (Reasoning) or ZAYA1-8B?
The published evidence does not provide a shared weighted coding basis for both models, so BenchLM does not name a coding winner.
Which is better for agentic tasks, Kimi K2.5 (Reasoning) or ZAYA1-8B?
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, Kimi K2.5 (Reasoning) 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, Kimi K2.5 (Reasoning) or ZAYA1-8B?
Kimi K2.5 (Reasoning) has the larger documented context window: 256K, compared with 131K.
Related comparisons
Last updated August 5, 2026
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