Agentic
Not comparable- Hy-MT1.5-1.8B-1.25bit
- Not measured
- Kimi K2.5
- 55.0
- Weighted basis
- 0 vs 2 rows
- Reading
- Not comparable
Model comparison
Hy-MT1.5-1.8B-1.25bit vs Kimi K2.5
Updated August 3, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.
The public evidence has no benchmark result shared by both models, so it does not support a quality verdict. Use the documented cost, context, and runtime rows instead.
0 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
Hy-MT1.5-1.8B-1.25bit
Hy-MT1.5-1.8B-1.25bit 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
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.
45 Kimi K2.5 only
- Shared results
- 0
- Hy-MT1.5-1.8B-1.25bit only
- 0
- Kimi K2.5 only
- 45
- Like-for-like categories
- 0 / 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.
Coding
Not comparable- Hy-MT1.5-1.8B-1.25bit
- Not measured
- Kimi K2.5
- 59.4
- Weighted basis
- 0 vs 4 rows
- Reading
- Not comparable
Reasoning
Not comparable- Hy-MT1.5-1.8B-1.25bit
- Not measured
- Kimi K2.5
- 61.0
- Weighted basis
- 0 vs 1 rows
- Reading
- Not comparable
Knowledge
Not comparable- Hy-MT1.5-1.8B-1.25bit
- Not measured
- Kimi K2.5
- 56.9
- Weighted basis
- 0 vs 4 rows
- Reading
- Not comparable
Math
Not comparable- Hy-MT1.5-1.8B-1.25bit
- Not measured
- Kimi K2.5
- 60.6
- Weighted basis
- 0 vs 4 rows
- Reading
- Not comparable
Multilingual
Not comparable- Hy-MT1.5-1.8B-1.25bit
- Not measured
- Kimi K2.5
- 82.3
- Weighted basis
- 0 vs 1 rows
- Reading
- Not comparable
Multimodal
Not comparable- Hy-MT1.5-1.8B-1.25bit
- Not measured
- Kimi K2.5
- 78.5
- Weighted basis
- 0 vs 1 rows
- Reading
- Not comparable
Instruction following
Not comparable- Hy-MT1.5-1.8B-1.25bit
- Not measured
- Kimi K2.5
- 93.9
- Weighted basis
- 0 vs 1 rows
- Reading
- Not comparable
| Category | Hy-MT1.5-1.8B-1.25bit | Kimi K2.5 | Weighted basis | Reading |
|---|---|---|---|---|
| Agentic | Not measured | 55.0 | Not comparable0 vs 2 rows | Not comparable |
| Coding | Not measured | 59.4 | Not comparable0 vs 4 rows | Not comparable |
| Reasoning | Not measured | 61.0 | Not comparable0 vs 1 rows | Not comparable |
| Knowledge | Not measured | 56.9 | Not comparable0 vs 4 rows | Not comparable |
| Math | Not measured | 60.6 | Not comparable0 vs 4 rows | Not comparable |
| Multilingual | Not measured | 82.3 | Not comparable0 vs 1 rows | Not comparable |
| Multimodal | Not measured | 78.5 | Not comparable0 vs 1 rows | Not comparable |
| Instruction following | Not measured | 93.9 | Not comparable0 vs 1 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.
A shared-evidence shape is not available.
BenchLM does not draw a radar or infer missing axes when the matched evidence is too sparse.
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
- Hy-MT1.5-1.8B-1.25bit
- API rate not published
- Fits in one request
- Kimi K2.5
- $0.0021
- Fits in one request
Hy-MT1.5-1.8B-1.25bit has no comparable published API token rate.
Repository review
50K fresh input + 3K output tokens
- Hy-MT1.5-1.8B-1.25bit
- API rate not published
- Fits in one request
- Kimi K2.5
- $0.039
- Fits in one request
Hy-MT1.5-1.8B-1.25bit has no comparable published API token rate.
Cache-heavy agent loop
200K cached + 20K fresh input + 10K output tokens
- Hy-MT1.5-1.8B-1.25bit
- API rate not published
- Fits in one request
- Cached-input rate unavailable
- Kimi K2.5
- $0.162
- Fits in one request
- Cached input priced at the published list-input rate
Kimi K2.5 has no published cached-input rate, so cached tokens use its listed input rate. Hy-MT1.5-1.8B-1.25bit 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.
SpecificationHy-MT1.5-1.8B-1.25bitKimi K2.5
Context window
Maximum documented context; output-token limits may be lower.
Hy-MT1.5-1.8B-1.25bit
262K
Kimi K2.5
256K
API model ID
Hy-MT1.5-1.8B-1.25bit
Not sourced
Kimi K2.5
Not sourced
Cached-input rate
A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.
Hy-MT1.5-1.8B-1.25bit
No comparable hosted API rate
Kimi K2.5
Not published
Documented inputs
Hy-MT1.5-1.8B-1.25bit
Not sourced
Kimi K2.5
Not sourced
Documented outputs
Hy-MT1.5-1.8B-1.25bit
Not sourced
Kimi K2.5
Not sourced
Provider availability
Hy-MT1.5-1.8B-1.25bit
Not sourced
Kimi K2.5
Not sourced
Reasoning profile
Hy-MT1.5-1.8B-1.25bit
Non-Reasoning
Kimi K2.5
Non-Reasoning
Weight access
Hy-MT1.5-1.8B-1.25bit
Open Weight
Kimi K2.5
Open Weight
License
Hy-MT1.5-1.8B-1.25bit
Open Weight
Kimi K2.5
Open Weight
Release date
Hy-MT1.5-1.8B-1.25bit
2026-04-29
Kimi K2.5
2026-02-01
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
- The public evidence has no benchmark result shared by both models, so it does not support a quality verdict.
- Workload cost
- A complete comparable API-rate estimate is not available for both models.
- Context tradeoff
- Hy-MT1.5-1.8B-1.25bit has the larger documented window (262K).
Run the same representative tasks against both endpoints before changing production traffic.
Self-host vs API cost
Estimates at 50,000 req/day · 1000 tokens/req average.
Hy-MT1.5-1.8B-1.25bit
API / mo$0
Self-host / moNot listed
Break-even—
Proprietary model — self-hosting not applicable.
Kimi K2.5
API / mo$2,700
Self-host / mo$5,221
Break-even132M/day
Benchmark evidence
The full public result ledger is available for audit without forcing a wide desktop table onto a phone.
Browse raw public benchmark evidence45 rows
Agentic
Terminal-Bench 2.0
Hy-MT1.5-1.8B-1.25bit—Kimi K2.550.8%SourceNot directly comparable
BrowseComp
Hy-MT1.5-1.8B-1.25bit—Kimi K2.560.6%SourceNot directly comparable
Claw-Eval
Hy-MT1.5-1.8B-1.25bit—Kimi K2.552.3%SourceNot directly comparable
QwenClawBench
Hy-MT1.5-1.8B-1.25bit—Kimi K2.554.3%SourceNot directly comparable
τ³-bench results
Hy-MT1.5-1.8B-1.25bit—Kimi K2.565.7%SourceNot directly comparable
DeepSearchQA
Hy-MT1.5-1.8B-1.25bit—Kimi K2.577.1%SourceNot directly comparable
DeepPlanning
Hy-MT1.5-1.8B-1.25bit—Kimi K2.514.4%SourceNot directly comparable
Toolathlon
Hy-MT1.5-1.8B-1.25bit—Kimi K2.527.8%SourceNot directly comparable
MCP Atlas
Hy-MT1.5-1.8B-1.25bit—Kimi K2.529.5%SourceNot directly comparable
MCP-Tasks
Hy-MT1.5-1.8B-1.25bit—Kimi K2.559.1%SourceNot directly comparable
WideResearch
Hy-MT1.5-1.8B-1.25bit—Kimi K2.572.7%SourceNot directly comparable
Gert Labs
Hy-MT1.5-1.8B-1.25bit—Kimi K2.545.88%SourceNot directly comparable
ResearchClawBench
Hy-MT1.5-1.8B-1.25bit—Kimi K2.514.0%SourceNot directly comparable
JobBench
Hy-MT1.5-1.8B-1.25bit—Kimi K2.58.7%SourceNot directly comparable
Coding
SWE-bench Verified
Hy-MT1.5-1.8B-1.25bit—Kimi K2.576.8%SourceNot directly comparable
SWE-bench Verified*
Hy-MT1.5-1.8B-1.25bit—Kimi K2.570.8%SourceNot directly comparable
LiveCodeBench v6
Hy-MT1.5-1.8B-1.25bit—Kimi K2.585.0%SourceNot directly comparable
SWE-bench Pro
Hy-MT1.5-1.8B-1.25bit—Kimi K2.550.7%SourceNot directly comparable
SWE Multilingual
Hy-MT1.5-1.8B-1.25bit—Kimi K2.573%SourceNot directly comparable
SWE-Rebench
Hy-MT1.5-1.8B-1.25bit—Kimi K2.558.5%SourceNot directly comparable
React Native Evals
Hy-MT1.5-1.8B-1.25bit—Kimi K2.577.2%SourceNot directly comparable
SciCode
Hy-MT1.5-1.8B-1.25bit—Kimi K2.548.7%SourceNot directly comparable
Reasoning
LongBench v2
Hy-MT1.5-1.8B-1.25bit—Kimi K2.561%SourceNot directly comparable
Knowledge
GPQA
Hy-MT1.5-1.8B-1.25bit—Kimi K2.587.6%SourceNot directly comparable
GPQA-D
Hy-MT1.5-1.8B-1.25bit—Kimi K2.587.6%SourceNot directly comparable
SuperGPQA
Hy-MT1.5-1.8B-1.25bit—Kimi K2.569.2%SourceNot directly comparable
MMLU-Pro
Hy-MT1.5-1.8B-1.25bit—Kimi K2.587.1%SourceNot directly comparable
MMLU-Pro (Arcee)
Hy-MT1.5-1.8B-1.25bit—Kimi K2.587.1%SourceNot directly comparable
HLE
Hy-MT1.5-1.8B-1.25bit—Kimi K2.530.1%SourceNot directly comparable
Math
AIME 2025
Hy-MT1.5-1.8B-1.25bit—Kimi K2.596.1%SourceNot directly comparable
AIME26
Hy-MT1.5-1.8B-1.25bit—Kimi K2.595.8%SourceNot directly comparable
AIME25 (Arcee)
Hy-MT1.5-1.8B-1.25bit—Kimi K2.596.3%SourceNot directly comparable
HMMT Feb 2025
Hy-MT1.5-1.8B-1.25bit—Kimi K2.595.4%SourceNot directly comparable
HMMT Nov 2025
Hy-MT1.5-1.8B-1.25bit—Kimi K2.591.1%SourceNot directly comparable
HMMT Feb 2026
Hy-MT1.5-1.8B-1.25bit—Kimi K2.587.1%SourceNot directly comparable
MMAnswerBench
Hy-MT1.5-1.8B-1.25bit—Kimi K2.581.8%SourceNot directly comparable
FrontierMath v2 (Tiers 1-3)
Hy-MT1.5-1.8B-1.25bit—Kimi K2.527.900%SourceNot directly comparable
FrontierMath v2 (Tier 4)
Hy-MT1.5-1.8B-1.25bit—Kimi K2.54.200%SourceNot directly comparable
Multilingual
Multimodal
Instruction following
IFEval
Hy-MT1.5-1.8B-1.25bit—Kimi K2.593.9%SourceNot directly comparable
Frequently asked questions
Which is better, Hy-MT1.5-1.8B-1.25bit or Kimi K2.5?
The public evidence has no benchmark result shared by both models, so it does not support a quality verdict. The page therefore keeps the decision tied to the specific documented workload.
Which is better for coding, Hy-MT1.5-1.8B-1.25bit or Kimi K2.5?
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, Hy-MT1.5-1.8B-1.25bit or Kimi K2.5?
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, Hy-MT1.5-1.8B-1.25bit or Kimi K2.5?
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, Hy-MT1.5-1.8B-1.25bit or Kimi K2.5?
Hy-MT1.5-1.8B-1.25bit has the larger documented context window: 262K, compared with 256K.
Related comparisons
Last updated August 3, 2026
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