Agentic
Directional only- Grok 4.5
- 83.3
- Kimi K2.5
- 55.0
- Weighted basis
- 1 vs 2 rows
- Reading
- Directional only
Grok 4.5 vs Kimi K2.5
Updated August 22, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.
Decision reading
Grok 4.5 has the higher public score, 75.19 versus 58.68, and the 90% score intervals do not overlap.
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
Grok 4.5
Grok 4.5 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
Grok 4.5
Grok 4.5 has the lower estimated token cost for this stated workload. 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
The category averages use different weighted benchmark sets, so they are directional rather than like-for-like.
Confidence: limited
Agentic work
Tool use, computer use, and multi-step task completion
Not enough matched evidence
The category averages use different weighted benchmark sets, so they are directional rather than like-for-like.
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.
7 Grok 4.5 only
3 Shared
42 Kimi K2.5 only
- Shared results
- 3
- Grok 4.5 only
- 7
- Kimi K2.5 only
- 42
- Like-for-like categories
- 0 / 8
2 categories use 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.
Coding
Directional only- Grok 4.5
- 64.7
- Kimi K2.5
- 59.4
- Weighted basis
- 1 vs 4 rows
- Reading
- Directional only
Reasoning
Not comparable- Grok 4.5
- 52.6
- Kimi K2.5
- 61.0
- Weighted basis
- 1 vs 1 rows
- Reading
- Not comparable
Knowledge
Not comparable- Grok 4.5
- Not measured
- Kimi K2.5
- 56.9
- Weighted basis
- 0 vs 4 rows
- Reading
- Not comparable
Math
Not comparable- Grok 4.5
- Not measured
- Kimi K2.5
- 60.6
- Weighted basis
- 0 vs 4 rows
- Reading
- Not comparable
Multilingual
Not comparable- Grok 4.5
- Not measured
- Kimi K2.5
- 82.3
- Weighted basis
- 0 vs 1 rows
- Reading
- Not comparable
Multimodal
Not comparable- Grok 4.5
- Not measured
- Kimi K2.5
- 78.5
- Weighted basis
- 0 vs 1 rows
- Reading
- Not comparable
Instruction following
Not comparable- Grok 4.5
- Not measured
- Kimi K2.5
- 93.9
- Weighted basis
- 0 vs 1 rows
- Reading
- Not comparable
| Category | Grok 4.5 | Kimi K2.5 | Weighted basis | Reading |
|---|---|---|---|---|
| Agentic | 83.3 | 55.0 | Directional only1 vs 2 rows | Directional only |
| Coding | 64.7 | 59.4 | Directional only1 vs 4 rows | Directional only |
| Reasoning | 52.6 | 61.0 | Not comparable1 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.
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.
Terminal-Bench 2.0
Agentic
SWE-bench Pro
Coding
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
- Grok 4.5
- $0.005
- 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
- Grok 4.5
- $0.118
- 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
- Grok 4.5
- $0.16
- Fits in one request
- Kimi K2.5
- $0.162
- Fits in one request
- Cached input priced at the published list-input rate
Grok 4.5 has the lower modeled cost
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.
SpecificationGrok 4.5Kimi K2.5
Context window
Maximum documented context; output-token limits may be lower.
Grok 4.5
500K
Kimi K2.5
256K
API model ID
Grok 4.5
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.
Grok 4.5
$0.3 per 1M cached input tokens
Kimi K2.5
Not published
Documented inputs
Grok 4.5
Not sourced
Kimi K2.5
Not sourced
Documented outputs
Grok 4.5
Not sourced
Kimi K2.5
Not sourced
Provider availability
Grok 4.5
Not sourced
Kimi K2.5
Not sourced
Reasoning profile
Grok 4.5
Reasoning
Kimi K2.5
Non-Reasoning
Weight access
Grok 4.5
Proprietary
Kimi K2.5
Open Weight
License
Grok 4.5
Proprietary
Kimi K2.5
Open Weight
Release date
Grok 4.5
2026-07-08
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
- Grok 4.5 has the higher public score, 75.19 versus 58.68, and the 90% score intervals do not overlap.
- Workload cost
- Repository review: $0.118 vs $0.039. Cache-heavy agent loop: $0.16 vs $0.162.
- Context tradeoff
- Grok 4.5 has the larger documented window (500K).
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.
Grok 4.5
API / mo$6,000
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 evidence52 rows
Agentic
Terminal-Bench 3.0
Grok 4.515.7%SourceKimi K2.5—Not directly comparable
Terminal-Bench 2.0
Grok 4.583.3%SourceKimi K2.550.8%SourceGrok 4.5 leads this result
deepSwe
Grok 4.553%SourceKimi K2.5—Not directly comparable
BrowseComp
Grok 4.5—Kimi K2.560.6%SourceNot directly comparable
Claw-Eval
Grok 4.5—Kimi K2.552.3%SourceNot directly comparable
QwenClawBench
Grok 4.5—Kimi K2.554.3%SourceNot directly comparable
τ³-bench results
Grok 4.5—Kimi K2.565.7%SourceNot directly comparable
DeepSearchQA
Grok 4.5—Kimi K2.577.1%SourceNot directly comparable
DeepPlanning
Grok 4.5—Kimi K2.514.4%SourceNot directly comparable
Toolathlon
Grok 4.5—Kimi K2.527.8%SourceNot directly comparable
MCP Atlas
Grok 4.5—Kimi K2.529.5%SourceNot directly comparable
MCP-Tasks
Grok 4.5—Kimi K2.559.1%SourceNot directly comparable
WideResearch
Grok 4.5—Kimi K2.572.7%SourceNot directly comparable
Gert Labs
Grok 4.5—Kimi K2.545.88%SourceNot directly comparable
ResearchClawBench
Grok 4.5—Kimi K2.514.0%SourceNot directly comparable
JobBench
Grok 4.5—Kimi K2.58.7%SourceNot directly comparable
Coding
SWE-bench Pro
Grok 4.564.7%SourceKimi K2.550.7%SourceGrok 4.5 leads this result
SWE Multilingual
Grok 4.578%SourceKimi K2.573%SourceGrok 4.5 leads this result
Terminal-Bench 2.0
Grok 4.583.3%SourceKimi K2.5—Not directly comparable
cursorBench32
Grok 4.566.7%SourceKimi K2.5—Not directly comparable
VulcanBench v3
Grok 4.591.3%SourceKimi K2.5—Not directly comparable
SWE-bench Verified
Grok 4.5—Kimi K2.576.8%SourceNot directly comparable
SWE-bench Verified*
Grok 4.5—Kimi K2.570.8%SourceNot directly comparable
LiveCodeBench v6
Grok 4.5—Kimi K2.585.0%SourceNot directly comparable
SWE-Rebench
Grok 4.5—Kimi K2.558.5%SourceNot directly comparable
React Native Evals
Grok 4.5—Kimi K2.577.2%SourceNot directly comparable
SciCode
Grok 4.5—Kimi K2.548.7%SourceNot directly comparable
Reasoning
Knowledge
GPQA
Grok 4.5—Kimi K2.587.6%SourceNot directly comparable
GPQA-D
Grok 4.5—Kimi K2.587.6%SourceNot directly comparable
SuperGPQA
Grok 4.5—Kimi K2.569.2%SourceNot directly comparable
MMLU-Pro
Grok 4.5—Kimi K2.587.1%SourceNot directly comparable
MMLU-Pro (Arcee)
Grok 4.5—Kimi K2.587.1%SourceNot directly comparable
HLE
Grok 4.5—Kimi K2.530.1%SourceNot directly comparable
Math
AIME 2025
Grok 4.5—Kimi K2.596.1%SourceNot directly comparable
AIME26
Grok 4.5—Kimi K2.595.8%SourceNot directly comparable
AIME25 (Arcee)
Grok 4.5—Kimi K2.596.3%SourceNot directly comparable
HMMT Feb 2025
Grok 4.5—Kimi K2.595.4%SourceNot directly comparable
HMMT Nov 2025
Grok 4.5—Kimi K2.591.1%SourceNot directly comparable
HMMT Feb 2026
Grok 4.5—Kimi K2.587.1%SourceNot directly comparable
MMAnswerBench
Grok 4.5—Kimi K2.581.8%SourceNot directly comparable
FrontierMath v2 (Tiers 1-3)
Grok 4.5—Kimi K2.527.900%SourceNot directly comparable
FrontierMath v2 (Tier 4)
Grok 4.5—Kimi K2.54.200%SourceNot directly comparable
Multilingual
Multimodal
Instruction following
IFEval
Grok 4.5—Kimi K2.593.9%SourceNot directly comparable
Frequently asked questions
Which is better, Grok 4.5 or Kimi K2.5?
Grok 4.5 has the higher public score, 75.19 versus 58.68, 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, Grok 4.5 or Kimi K2.5?
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.
Which is better for agentic tasks, Grok 4.5 or Kimi K2.5?
The current agentic tasks 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.
Which costs less, Grok 4.5 or Kimi K2.5?
For the stated presets, chat costs $0.005 on Grok 4.5 and $0.0021 on Kimi K2.5; repository review costs $0.118 and $0.039; the cache-heavy agent loop costs $0.16 and $0.162. Kimi K2.5 has no published cached-input rate, so cached tokens use its listed input rate.
Which has the larger context window, Grok 4.5 or Kimi K2.5?
Grok 4.5 has the larger documented context window: 500K, compared with 256K.
Related comparisons
Last updated August 22, 2026
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