Agentic
Like-for-like- Inkling
- 69.4
- Kimi K3
- 89.5
- Weighted basis
- 2 vs 2 rows
- Reading
- Kimi K3 leads
Inkling vs Kimi K3
Updated August 19, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.
Decision reading
Kimi K3 has the higher public score, 80.53 versus 67.06, and the 90% score intervals do not overlap.
10 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.
Agentic work
Tool use, computer use, and multi-step task completion
Kimi K3
Kimi K3 leads on the same 2 weighted benchmark rows.
Confidence: limited
Long documents
Prompts that approach the documented context limit
Kimi K3
Kimi K3 has the larger documented context window.
Confidence: documented
Chat turn cost
1K fresh input + 500 output tokens
Inkling
Inkling has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Confidence: listed-rates
Show secondary and unsupported calls
Cache-heavy agent loop cost
200K cached + 20K fresh input + 10K output tokens
Inkling
Inkling has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Confidence: listed-rates
Repository review cost
50K fresh input + 3K output tokens
Inkling
Inkling 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
What is actually comparable
Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.
5 Inkling only
10 Shared
30 Kimi K3 only
- Shared results
- 10
- Inkling only
- 5
- Kimi K3 only
- 30
- Like-for-like categories
- 2 / 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
Like-for-like- Inkling
- 51.6
- Kimi K3
- 61.0
- Weighted basis
- 2 vs 2 rows
- Reading
- Kimi K3 leads
Multimodal
Directional only- Inkling
- 76.5
- Kimi K3
- 78.5
- Weighted basis
- 2 vs 3 rows
- Reading
- Directional only
Coding
Not comparable- Inkling
- 68.6
- Kimi K3
- Not measured
- Weighted basis
- 2 vs 0 rows
- Reading
- Not comparable
Reasoning
Not comparable- Inkling
- Not measured
- Kimi K3
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
Math
Not comparable- Inkling
- 97.1
- Kimi K3
- Not measured
- Weighted basis
- 1 vs 0 rows
- Reading
- Not comparable
Multilingual
Not comparable- Inkling
- Not measured
- Kimi K3
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
Instruction following
Not comparable- Inkling
- 79.8
- Kimi K3
- Not measured
- Weighted basis
- 1 vs 0 rows
- Reading
- Not comparable
| Category | Inkling | Kimi K3 | Weighted basis | Reading |
|---|---|---|---|---|
| Agentic | 69.4 | 89.5 | Like-for-like2 vs 2 rows | Kimi K3 leads |
| Knowledge | 51.6 | 61.0 | Like-for-like2 vs 2 rows | Kimi K3 leads |
| Multimodal | 76.5 | 78.5 | Directional only2 vs 3 rows | Directional only |
| Coding | 68.6 | Not measured | Not comparable2 vs 0 rows | Not comparable |
| Reasoning | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
| Math | 97.1 | Not measured | Not comparable1 vs 0 rows | Not comparable |
| Multilingual | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
| Instruction following | 79.8 | Not measured | Not comparable1 vs 0 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
BrowseComp
Agentic
HLE
Knowledge
CharXiv
Multimodal
MMMU-Pro
Multimodal
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
- Inkling
- $0.00421
- Fits in one request
- Kimi K3
- $0.0105
- Fits in one request
Inkling has the lower modeled cost
Costs use the listed standard API rates.
Repository review
50K fresh input + 3K output tokens
- Inkling
- $0.10754
- Fits in one request
- Kimi K3
- $0.195
- Fits in one request
Inkling has the lower modeled cost
Costs use the listed standard API rates.
Cache-heavy agent loop
200K cached + 20K fresh input + 10K output tokens
- Inkling
- $0.159
- Fits in one request
- Kimi K3
- $0.27
- Fits in one request
Inkling has the lower modeled cost
Costs use the listed standard API rates.
Specification differences
Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.
SpecificationInklingKimi K3
Context window
Maximum documented context; output-token limits may be lower.
Inkling
1M
Kimi K3
1.05M
API model ID
Inkling
Not sourced
Kimi K3
Not sourced
Cached-input rate
A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.
Inkling
$0.374 per 1M cached input tokens
Kimi K3
$0.3 per 1M cached input tokens
Documented inputs
Inkling
Not sourced
Kimi K3
Not sourced
Documented outputs
Inkling
Not sourced
Kimi K3
Not sourced
Provider availability
Inkling
Not sourced
Kimi K3
Not sourced
Reasoning profile
Inkling
Hybrid
Kimi K3
Reasoning
Weight access
Inkling
Open Weight
Kimi K3
Pending
License
Inkling
Open Weight
Kimi K3
Pending
Release date
Inkling
2026-07-15
Kimi K3
2026-07-16
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 K3 has the higher public score, 80.53 versus 67.06, and the 90% score intervals do not overlap.
- Workload cost
- Repository review: $0.10754 vs $0.195. Cache-heavy agent loop: $0.159 vs $0.27.
- Context tradeoff
- Kimi K3 has the larger documented window (1.05M).
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 evidence45 rows
Agentic
Terminal-Bench 2.0
Inkling63.8%SourceKimi K388.3%SourceKimi K3 leads this result
BrowseComp
Inkling77.1%SourceKimi K391.2%SourceKimi K3 leads this result
MCP Atlas
Inkling74.1%SourceKimi K384.2%SourceKimi K3 leads this result
DeepSearchQA
Inkling—Kimi K395.0%SourceNot directly comparable
Toolathlon-Verified
Inkling—Kimi K373.2%SourceNot directly comparable
AutomationBench
Inkling—Kimi K330.8%SourceNot directly comparable
JobBench
Inkling—Kimi K352.9%SourceNot directly comparable
APEX-Agents
Inkling—Kimi K337.6%SourceNot directly comparable
SpreadsheetBench 2
Inkling—Kimi K334.8%SourceNot directly comparable
DECK-Bench
Inkling—Kimi K373.5%SourceNot directly comparable
Coding
SWE-bench Verified
Inkling77.6%SourceKimi K3—Not directly comparable
SWE-bench Pro
Inkling54.3%SourceKimi K3—Not directly comparable
Terminal-Bench 2.0
Inkling63.8%SourceKimi K3—Not directly comparable
deepSwe
Inkling—Kimi K367.5%SourceNot directly comparable
cursorBench32
Inkling—Kimi K360.8%SourceNot directly comparable
FrontierSWE
Inkling—Kimi K381.2%SourceNot directly comparable
ProgramBench
Inkling—Kimi K377.8%SourceNot directly comparable
Kimi Code Bench v2
Inkling—Kimi K372.9%SourceNot directly comparable
sweMarathon
Inkling—Kimi K342%SourceNot directly comparable
PostTrain Bench
Inkling—Kimi K336.6%SourceNot directly comparable
MLS-Bench Lite
Inkling—Kimi K348.3%SourceNot directly comparable
VulcanBench v3
Inkling—Kimi K373.9%SourceNot directly comparable
APEX-SWE
Inkling—Kimi K348.0%SourceNot directly comparable
EEBench
Inkling—Kimi K338.3%SourceNot directly comparable
InferenceEval
Inkling—Kimi K339.8%SourceNot directly comparable
KernelBench Internal
Inkling—Kimi K368.5%SourceNot directly comparable
Knowledge
Math
AIME26
Inkling97.1%SourceKimi K3—Not directly comparable
Multimodal
MMMU-Pro
Inkling73.5%SourceKimi K381.6%SourceKimi K3 leads this result
CharXiv
Inkling82%SourceKimi K391.3%SourceKimi K3 leads this result
CharXiv w/o tools
Inkling78.1%SourceKimi K384.8%SourceKimi K3 leads this result
OfficeQA Pro
Inkling—Kimi K363.3%SourceNot directly comparable
MMMU-Pro w/ Python
Inkling—Kimi K383.4%SourceNot directly comparable
MathVision
Inkling—Kimi K394.3%SourceNot directly comparable
MathVision w/ Python
Inkling—Kimi K397.8%SourceNot directly comparable
BabyVision w/ Python
Inkling—Kimi K385.7%SourceNot directly comparable
ZeroBench
Inkling—Kimi K323.0%SourceNot directly comparable
ZeroBench w/ Python
Inkling—Kimi K341.0%SourceNot directly comparable
WorldVQA ForceAnswer
Inkling—Kimi K351.0%SourceNot directly comparable
OmniDocBench
Inkling—Kimi K391.1%SourceNot directly comparable
PerceptionBench
Inkling—Kimi K358.5%SourceNot directly comparable
Instruction following
IFBench
Inkling79.8%SourceKimi K3—Not directly comparable
Frequently asked questions
Which is better, Inkling or Kimi K3?
Kimi K3 has the higher public score, 80.53 versus 67.06, 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, Inkling or Kimi K3?
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, Inkling or Kimi K3?
Kimi K3 leads the like-for-like agentic tasks comparison across 2 shared weighted benchmark rows.
Which costs less, Inkling or Kimi K3?
For the stated presets, chat costs $0.00421 on Inkling and $0.0105 on Kimi K3; repository review costs $0.10754 and $0.195; the cache-heavy agent loop costs $0.159 and $0.27. Costs use the listed standard API rates.
Which has the larger context window, Inkling or Kimi K3?
Kimi K3 has the larger documented context window: 1.05M, compared with 1M.
Related comparisons
Last updated August 19, 2026
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