Multimodal
Like-for-like- Interfaze Beta
- 71.1
- Kimi K2.5
- 78.5
- Weighted basis
- 1 vs 1 rows
- Reading
- Kimi K2.5 leads
Model comparison
Interfaze Beta vs Kimi K2.5
Updated August 10, 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.
3 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
Interfaze Beta
Interfaze Beta has the larger documented context window.
Confidence: documented
Chat turn cost
1K fresh input + 500 output tokens
Kimi K2.5
Kimi K2.5 has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Confidence: listed-rates
Cache-heavy agent loop cost
200K cached + 20K fresh input + 10K output tokens
Kimi K2.5
Kimi K2.5 has the lower estimated token cost for this stated workload. Interfaze Beta has no published cached-input rate, so cached tokens use its listed input rate. Kimi K2.5 has no published cached-input rate, so cached tokens use its listed input rate.
Confidence: rate-fallback
Show secondary and unsupported calls
Repository review cost
50K fresh input + 3K output tokens
Kimi K2.5
Kimi K2.5 has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Confidence: listed-rates
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
What is actually comparable
Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.
6 Interfaze Beta only
3 Shared
42 Kimi K2.5 only
- Shared results
- 3
- Interfaze Beta only
- 6
- Kimi K2.5 only
- 42
- 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- Interfaze Beta
- 89.9
- Kimi K2.5
- 56.9
- Weighted basis
- 1 vs 4 rows
- Reading
- Directional only
Agentic
Not comparable- Interfaze Beta
- Not measured
- Kimi K2.5
- 55.0
- Weighted basis
- 0 vs 2 rows
- Reading
- Not comparable
Coding
Not comparable- Interfaze Beta
- Not measured
- Kimi K2.5
- 59.4
- Weighted basis
- 0 vs 4 rows
- Reading
- Not comparable
Reasoning
Not comparable- Interfaze Beta
- Not measured
- Kimi K2.5
- 61.0
- Weighted basis
- 0 vs 1 rows
- Reading
- Not comparable
Math
Not comparable- Interfaze Beta
- Not measured
- Kimi K2.5
- 60.6
- Weighted basis
- 0 vs 4 rows
- Reading
- Not comparable
Multilingual
Not comparable- Interfaze Beta
- Not measured
- Kimi K2.5
- 82.3
- Weighted basis
- 0 vs 1 rows
- Reading
- Not comparable
Instruction following
Not comparable- Interfaze Beta
- Not measured
- Kimi K2.5
- 93.9
- Weighted basis
- 0 vs 1 rows
- Reading
- Not comparable
| Category | Interfaze Beta | Kimi K2.5 | Weighted basis | Reading |
|---|---|---|---|---|
| Multimodal | 71.1 | 78.5 | Like-for-like1 vs 1 rows | Kimi K2.5 leads |
| Knowledge | 89.9 | 56.9 | Directional only1 vs 4 rows | Directional only |
| 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 |
| Math | Not measured | 60.6 | Not comparable0 vs 4 rows | Not comparable |
| Multilingual | Not measured | 82.3 | 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.
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.
MMMU-Pro
Multimodal
GPQA
Knowledge
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
- Interfaze Beta
- $0.00325
- Fits in one request
- Kimi K2.5
- $0.0021
- Fits in one request
Kimi K2.5 has the lower modeled cost
Costs use the listed standard API rates.
Repository review
50K fresh input + 3K output tokens
- Interfaze Beta
- $0.0855
- Fits in one request
- Kimi K2.5
- $0.039
- Fits in one request
Kimi K2.5 has the lower modeled cost
Costs use the listed standard API rates.
Cache-heavy agent loop
200K cached + 20K fresh input + 10K output tokens
- Interfaze Beta
- $0.365
- Fits in one request
- Cached input priced at the published list-input rate
- Kimi K2.5
- $0.162
- Fits in one request
- Cached input priced at the published list-input rate
Kimi K2.5 has the lower modeled cost
Interfaze Beta has no published cached-input rate, so cached tokens use its listed input rate. Kimi K2.5 has no published cached-input rate, so cached tokens use its listed input rate.
Specification differences
Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.
SpecificationInterfaze BetaKimi K2.5
Context window
Maximum documented context; output-token limits may be lower.
Interfaze Beta
1M
Kimi K2.5
256K
API model ID
Interfaze Beta
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.
Interfaze Beta
Not published
Kimi K2.5
Not published
Documented inputs
Interfaze Beta
Not sourced
Kimi K2.5
Not sourced
Documented outputs
Interfaze Beta
Not sourced
Kimi K2.5
Not sourced
Provider availability
Interfaze Beta
Not sourced
Kimi K2.5
Not sourced
Reasoning profile
Interfaze Beta
Reasoning
Kimi K2.5
Non-Reasoning
Weight access
Interfaze Beta
Proprietary
Kimi K2.5
Open Weight
License
Interfaze Beta
Proprietary
Kimi K2.5
Open Weight
Release date
Interfaze Beta
2026-05-11
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
- 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
- Repository review: $0.0855 vs $0.039. Cache-heavy agent loop: $0.365 vs $0.162.
- Context tradeoff
- Interfaze Beta has the larger documented window (1M).
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.
Interfaze Beta
API / mo$3,750
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 evidence51 rows
Agentic
Terminal-Bench 2.0
Interfaze Beta—Kimi K2.550.8%SourceNot directly comparable
BrowseComp
Interfaze Beta—Kimi K2.560.6%SourceNot directly comparable
Claw-Eval
Interfaze Beta—Kimi K2.552.3%SourceNot directly comparable
QwenClawBench
Interfaze Beta—Kimi K2.554.3%SourceNot directly comparable
τ³-bench results
Interfaze Beta—Kimi K2.565.7%SourceNot directly comparable
DeepSearchQA
Interfaze Beta—Kimi K2.577.1%SourceNot directly comparable
DeepPlanning
Interfaze Beta—Kimi K2.514.4%SourceNot directly comparable
Toolathlon
Interfaze Beta—Kimi K2.527.8%SourceNot directly comparable
MCP Atlas
Interfaze Beta—Kimi K2.529.5%SourceNot directly comparable
MCP-Tasks
Interfaze Beta—Kimi K2.559.1%SourceNot directly comparable
WideResearch
Interfaze Beta—Kimi K2.572.7%SourceNot directly comparable
Gert Labs
Interfaze Beta—Kimi K2.545.88%SourceNot directly comparable
ResearchClawBench
Interfaze Beta—Kimi K2.514.0%SourceNot directly comparable
JobBench
Interfaze Beta—Kimi K2.58.7%SourceNot directly comparable
Coding
Spider 2.0-Lite
Interfaze Beta52.9%SourceKimi K2.5—Not directly comparable
SWE-bench Verified
Interfaze Beta—Kimi K2.576.8%SourceNot directly comparable
SWE-bench Verified*
Interfaze Beta—Kimi K2.570.8%SourceNot directly comparable
LiveCodeBench v6
Interfaze Beta—Kimi K2.585.0%SourceNot directly comparable
SWE-bench Pro
Interfaze Beta—Kimi K2.550.7%SourceNot directly comparable
SWE Multilingual
Interfaze Beta—Kimi K2.573%SourceNot directly comparable
SWE-Rebench
Interfaze Beta—Kimi K2.558.5%SourceNot directly comparable
React Native Evals
Interfaze Beta—Kimi K2.577.2%SourceNot directly comparable
SciCode
Interfaze Beta—Kimi K2.548.7%SourceNot directly comparable
Reasoning
LongBench v2
Interfaze Beta—Kimi K2.561%SourceNot directly comparable
Knowledge
GPQA
Interfaze Beta89.9%SourceKimi K2.587.6%SourceInterfaze Beta leads this result
GPQA-D
Interfaze Beta89.9%SourceKimi K2.587.6%SourceInterfaze Beta leads this result
MMMLU
Interfaze Beta90.9%SourceKimi K2.5—Not directly comparable
SuperGPQA
Interfaze Beta—Kimi K2.569.2%SourceNot directly comparable
MMLU-Pro
Interfaze Beta—Kimi K2.587.1%SourceNot directly comparable
MMLU-Pro (Arcee)
Interfaze Beta—Kimi K2.587.1%SourceNot directly comparable
HLE
Interfaze Beta—Kimi K2.530.1%SourceNot directly comparable
Math
AIME 2025
Interfaze Beta—Kimi K2.596.1%SourceNot directly comparable
AIME26
Interfaze Beta—Kimi K2.595.8%SourceNot directly comparable
AIME25 (Arcee)
Interfaze Beta—Kimi K2.596.3%SourceNot directly comparable
HMMT Feb 2025
Interfaze Beta—Kimi K2.595.4%SourceNot directly comparable
HMMT Nov 2025
Interfaze Beta—Kimi K2.591.1%SourceNot directly comparable
HMMT Feb 2026
Interfaze Beta—Kimi K2.587.1%SourceNot directly comparable
MMAnswerBench
Interfaze Beta—Kimi K2.581.8%SourceNot directly comparable
FrontierMath v2 (Tiers 1-3)
Interfaze Beta—Kimi K2.527.900%SourceNot directly comparable
FrontierMath v2 (Tier 4)
Interfaze Beta—Kimi K2.54.200%SourceNot directly comparable
Multilingual
Multimodal
OCRBench V2
Interfaze Beta70.7%SourceKimi K2.5—Not directly comparable
olmOCR
Interfaze Beta85.7%SourceKimi K2.5—Not directly comparable
RefCOCO (avg)
Interfaze Beta82.1%SourceKimi K2.5—Not directly comparable
MMMU-Pro
Interfaze Beta71.1%SourceKimi K2.578.5%SourceKimi K2.5 leads this result
Video-MME
Interfaze Beta—Kimi K2.587.4%SourceNot directly comparable
MMVU
Interfaze Beta—Kimi K2.580.4%SourceNot directly comparable
VideoMMMU
Interfaze Beta—Kimi K2.586.6%SourceNot directly comparable
Instruction following
Frequently asked questions
Which is better, Interfaze Beta or Kimi K2.5?
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, Interfaze Beta 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, Interfaze Beta 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, Interfaze Beta or Kimi K2.5?
For the stated presets, chat costs $0.00325 on Interfaze Beta and $0.0021 on Kimi K2.5; repository review costs $0.0855 and $0.039; the cache-heavy agent loop costs $0.365 and $0.162. Interfaze Beta has no published cached-input rate, so cached tokens use its listed input rate. Kimi K2.5 has no published cached-input rate, so cached tokens use its listed input rate.
Which has the larger context window, Interfaze Beta or Kimi K2.5?
Interfaze Beta has the larger documented context window: 1M, compared with 256K.
Related comparisons
Last updated August 10, 2026
Watch Interfaze Beta vs Kimi K2.5
One weekly email when material rank, price, or benchmark evidence changes make this matchup worth revisiting.
Read a sample issueJoin 2,000+ readers.