Agentic
Like-for-like- Inkling-Small
- 70.1
- Kimi K3
- 89.5
- Weighted basis
- 2 vs 2 rows
- Reading
- Kimi K3 leads
Model comparison
Updated July 30, 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.
11 results are shared. Category rows based on different benchmark sets are marked directional and do not name a winner.
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.
Tool use, computer use, and multi-step task completion
Kimi K3
Kimi K3 leads on the same 2 weighted benchmark rows.
Confidence: limited
Prompts that approach the documented context limit
Kimi K3
Kimi K3 has the larger documented context window.
Confidence: documented
1K fresh input + 500 output tokens
Inkling-Small
Inkling-Small has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Confidence: listed-rates
200K cached + 20K fresh input + 10K output tokens
Inkling-Small
Inkling-Small has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Confidence: listed-rates
50K fresh input + 3K output tokens
Inkling-Small
Inkling-Small has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Confidence: listed-rates
Code generation, repair, and software-engineering tasks
Not enough matched evidence
No shared weighted benchmark basis supports a winner.
Confidence: limited
Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.
1 category uses different evidence sets. Those rows remain visible for coverage context but do not name a winner.
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.
| Category | Inkling-Small | Kimi K3 | Weighted basis | Reading |
|---|---|---|---|---|
| Agentic | 70.1 | 89.5 | Like-for-like2 vs 2 rows | Kimi K3 leads |
| Knowledge | 53.4 | 61.0 | Like-for-like2 vs 2 rows | Kimi K3 leads |
| Multimodal | 76.6 | 78.5 | Directional only2 vs 3 rows | Directional only |
| Coding | 62.4 | Not measured | Not comparable3 vs 0 rows | Not comparable |
| Reasoning | 40.1 | Not measured | Not comparable1 vs 0 rows | Not comparable |
| Math | 92.9 | Not measured | Not comparable2 vs 0 rows | Not comparable |
| Multilingual | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
| Instruction following | 82.2 | Not measured | Not comparable1 vs 0 rows | Not comparable |
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
CharXiv
Multimodal
HLE
Knowledge
MMMU-Pro
Multimodal
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.
1K fresh input + 500 output tokens
Inkling-Small has the lower modeled cost
Costs use the listed standard API rates.
50K fresh input + 3K output tokens
Inkling-Small has the lower modeled cost
Costs use the listed standard API rates.
200K cached + 20K fresh input + 10K output tokens
Inkling-Small has the lower modeled cost
Costs use the listed standard API rates.
Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.
Maximum documented context; output-token limits may be lower.
Inkling-Small
1M
Kimi K3
1.05M
Inkling-Small
Not sourced
Kimi K3
Not sourced
A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.
Inkling-Small
$0.116 per 1M cached input tokens
Kimi K3
$0.3 per 1M cached input tokens
Inkling-Small
Not sourced
Kimi K3
Not sourced
Inkling-Small
Not sourced
Kimi K3
Not sourced
Inkling-Small
Not sourced
Kimi K3
Not sourced
Inkling-Small
Hybrid
Kimi K3
Reasoning
Inkling-Small
Open Weight
Kimi K3
Pending
Inkling-Small
Open Weight
Kimi K3
Pending
Inkling-Small
2026-07-30
Kimi K3
2026-07-16
Run the same representative tasks against both endpoints before changing production traffic.
The full public result ledger is available for audit without forcing a wide desktop table onto a phone.
Terminal-Bench 2.0
Kimi K3 leads this result
BrowseComp
Kimi K3 leads this result
MCP Atlas
Kimi K3 leads this result
Toolathlon-Verified
Kimi K3 leads this result
DeepSearchQA
Not directly comparable
AutomationBench
Not directly comparable
JobBench
Not directly comparable
APEX-Agents
Not directly comparable
SpreadsheetBench 2
Not directly comparable
DECK-Bench
Not directly comparable
SWE-bench Verified
Not directly comparable
SWE-bench Pro
Not directly comparable
Terminal-Bench 2.0
Not directly comparable
SciCode
Not directly comparable
deepSwe
Not directly comparable
FrontierSWE
Not directly comparable
ProgramBench
Not directly comparable
Kimi Code Bench v2
Not directly comparable
sweMarathon
Not directly comparable
PostTrain Bench
Not directly comparable
MLS-Bench Lite
Not directly comparable
VulcanBench v3
Not directly comparable
GPQA
Kimi K3 leads this result
GPQA-D
Kimi K3 leads this result
HLE
Kimi K3 leads this result
HLE w/o tools
Kimi K3 leads this result
MMMU-Pro
Kimi K3 leads this result
CharXiv
Kimi K3 leads this result
CharXiv w/o tools
Kimi K3 leads this result
OfficeQA Pro
Not directly comparable
MMMU-Pro w/ Python
Not directly comparable
MathVision
Not directly comparable
MathVision w/ Python
Not directly comparable
BabyVision w/ Python
Not directly comparable
ZeroBench
Not directly comparable
ZeroBench w/ Python
Not directly comparable
WorldVQA ForceAnswer
Not directly comparable
OmniDocBench
Not directly comparable
PerceptionBench
Not directly comparable
IFBench
Not directly comparable
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.
The published evidence does not provide a shared weighted coding basis for both models, so BenchLM does not name a coding winner.
Kimi K3 leads the like-for-like agentic tasks comparison across 2 shared weighted benchmark rows.
For the stated presets, chat costs $0.0013 on Inkling-Small and $0.0105 on Kimi K3; repository review costs $0.03332 and $0.195; the cache-heavy agent loop costs $0.0492 and $0.27. Costs use the listed standard API rates.
Kimi K3 has the larger documented context window: 1.05M, compared with 1M.
Last updated July 30, 2026
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