Agentic
Directional only- Gemini 3.5 Flash
- 77.2
- Kimi K3
- 89.5
- Weighted basis
- 2 vs 2 rows
- Reading
- Directional only
Gemini 3.5 Flash 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 64.69, and the 90% score intervals do not overlap.
8 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
Kimi K3
Kimi K3 has the larger documented context window.
Confidence: documented
Chat turn cost
1K fresh input + 500 output tokens
Gemini 3.5 Flash
Gemini 3.5 Flash 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
Gemini 3.5 Flash
Gemini 3.5 Flash 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
Repository review cost
50K fresh input + 3K output tokens
Gemini 3.5 Flash
Gemini 3.5 Flash 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
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.
15 Gemini 3.5 Flash only
8 Shared
32 Kimi K3 only
- Shared results
- 8
- Gemini 3.5 Flash only
- 15
- Kimi K3 only
- 32
- Like-for-like categories
- 0 / 8
3 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.
Knowledge
Directional only- Gemini 3.5 Flash
- 40.2
- Kimi K3
- 61.0
- Weighted basis
- 1 vs 2 rows
- Reading
- Directional only
Multimodal
Directional only- Gemini 3.5 Flash
- 83.8
- Kimi K3
- 78.5
- Weighted basis
- 2 vs 3 rows
- Reading
- Directional only
Coding
Not comparable- Gemini 3.5 Flash
- 55.1
- Kimi K3
- Not measured
- Weighted basis
- 1 vs 0 rows
- Reading
- Not comparable
Reasoning
Not comparable- Gemini 3.5 Flash
- 74.7
- Kimi K3
- Not measured
- Weighted basis
- 2 vs 0 rows
- Reading
- Not comparable
Math
Not comparable- Gemini 3.5 Flash
- 32.9
- Kimi K3
- Not measured
- Weighted basis
- 2 vs 0 rows
- Reading
- Not comparable
Multilingual
Not comparable- Gemini 3.5 Flash
- Not measured
- Kimi K3
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
Instruction following
Not comparable- Gemini 3.5 Flash
- Not measured
- Kimi K3
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
| Category | Gemini 3.5 Flash | Kimi K3 | Weighted basis | Reading |
|---|---|---|---|---|
| Agentic | 77.2 | 89.5 | Directional only2 vs 2 rows | Directional only |
| Knowledge | 40.2 | 61.0 | Directional only1 vs 2 rows | Directional only |
| Multimodal | 83.8 | 78.5 | Directional only2 vs 3 rows | Directional only |
| Coding | 55.1 | Not measured | Not comparable1 vs 0 rows | Not comparable |
| Reasoning | 74.7 | Not measured | Not comparable2 vs 0 rows | Not comparable |
| Math | 32.9 | Not measured | Not comparable2 vs 0 rows | Not comparable |
| Multilingual | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
| Instruction following | Not measured | Not measured | Not comparable0 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.
HLE
Knowledge
Terminal-Bench 2.0
Agentic
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
- Gemini 3.5 Flash
- $0.006
- Fits in one request
- Kimi K3
- $0.0105
- Fits in one request
Gemini 3.5 Flash has the lower modeled cost
Costs use the listed standard API rates.
Repository review
50K fresh input + 3K output tokens
- Gemini 3.5 Flash
- $0.102
- Fits in one request
- Kimi K3
- $0.195
- Fits in one request
Gemini 3.5 Flash has the lower modeled cost
Costs use the listed standard API rates.
Cache-heavy agent loop
200K cached + 20K fresh input + 10K output tokens
- Gemini 3.5 Flash
- $0.15
- Fits in one request
- Kimi K3
- $0.27
- Fits in one request
Gemini 3.5 Flash 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.
SpecificationGemini 3.5 FlashKimi K3
Context window
Maximum documented context; output-token limits may be lower.
Gemini 3.5 Flash
Kimi K3
1.05M
API model ID
Gemini 3.5 Flash
gemini-3.5-flash
Google Gemini API pricingKimi K3
Not sourced
Cached-input rate
A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.
Gemini 3.5 Flash
$0.15 per 1M cached input tokens
Google Gemini API pricingKimi K3
$0.3 per 1M cached input tokens
Documented inputs
Gemini 3.5 Flash
Not sourced
Kimi K3
Not sourced
Documented outputs
Gemini 3.5 Flash
Not sourced
Kimi K3
Not sourced
Provider availability
Gemini 3.5 Flash
Not sourced
Kimi K3
Not sourced
Reasoning profile
Gemini 3.5 Flash
Reasoning
Kimi K3
Reasoning
Weight access
Gemini 3.5 Flash
Proprietary
Kimi K3
Pending
License
Gemini 3.5 Flash
Proprietary
Kimi K3
Pending
Release date
Gemini 3.5 Flash
2026-05-19
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 64.69, and the 90% score intervals do not overlap.
- Workload cost
- Repository review: $0.102 vs $0.195. Cache-heavy agent loop: $0.15 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 evidence55 rows
Agentic
Terminal-Bench 2.0
Gemini 3.5 Flash76.2%SourceKimi K388.3%SourceKimi K3 leads this result
MCP Atlas
Gemini 3.5 Flash83.6%SourceKimi K384.2%SourceKimi K3 leads this result
Toolathlon
Gemini 3.5 Flash56.5%SourceKimi K3—Not directly comparable
OSWorld-Verified
Gemini 3.5 Flash78.4%SourceKimi K3—Not directly comparable
Finance Agent v2
Gemini 3.5 Flash57.9%SourceKimi K3—Not directly comparable
Gert Labs
Gemini 3.5 Flash61.85%SourceKimi K3—Not directly comparable
ResearchClawBench
Gemini 3.5 Flash18.0%SourceKimi K3—Not directly comparable
BrowseComp
Gemini 3.5 Flash—Kimi K391.2%SourceNot directly comparable
DeepSearchQA
Gemini 3.5 Flash—Kimi K395.0%SourceNot directly comparable
Toolathlon-Verified
Gemini 3.5 Flash—Kimi K373.2%SourceNot directly comparable
AutomationBench
Gemini 3.5 Flash—Kimi K330.8%SourceNot directly comparable
JobBench
Gemini 3.5 Flash—Kimi K352.9%SourceNot directly comparable
APEX-Agents
Gemini 3.5 Flash—Kimi K337.6%SourceNot directly comparable
SpreadsheetBench 2
Gemini 3.5 Flash—Kimi K334.8%SourceNot directly comparable
DECK-Bench
Gemini 3.5 Flash—Kimi K373.5%SourceNot directly comparable
Coding
Terminal-Bench 2.0
Gemini 3.5 Flash76.2%SourceKimi K3—Not directly comparable
SWE-bench Pro
Gemini 3.5 Flash55.1%SourceKimi K3—Not directly comparable
Vibe Code Bench
Gemini 3.5 Flash48.68%SourceKimi K3—Not directly comparable
cursorBench31
Gemini 3.5 Flash49.8%SourceKimi K3—Not directly comparable
cursorBench32
Shared sourceGemini 3.5 Flash48.8%Kimi K360.8%Kimi K3 leads this result
EEBench
Shared sourceGemini 3.5 Flash34.3%Kimi K338.3%Kimi K3 leads this result
deepSwe
Gemini 3.5 Flash—Kimi K367.5%SourceNot directly comparable
FrontierSWE
Gemini 3.5 Flash—Kimi K381.2%SourceNot directly comparable
ProgramBench
Gemini 3.5 Flash—Kimi K377.8%SourceNot directly comparable
Kimi Code Bench v2
Gemini 3.5 Flash—Kimi K372.9%SourceNot directly comparable
sweMarathon
Gemini 3.5 Flash—Kimi K342%SourceNot directly comparable
PostTrain Bench
Gemini 3.5 Flash—Kimi K336.6%SourceNot directly comparable
MLS-Bench Lite
Gemini 3.5 Flash—Kimi K348.3%SourceNot directly comparable
VulcanBench v3
Gemini 3.5 Flash—Kimi K373.9%SourceNot directly comparable
APEX-SWE
Gemini 3.5 Flash—Kimi K348.0%SourceNot directly comparable
InferenceEval
Gemini 3.5 Flash—Kimi K339.8%SourceNot directly comparable
KernelBench Internal
Gemini 3.5 Flash—Kimi K368.5%SourceNot directly comparable
Reasoning
Knowledge
Math
Multimodal
CharXiv
Gemini 3.5 Flash84.2%SourceKimi K391.3%SourceKimi K3 leads this result
MMMU-Pro
Gemini 3.5 Flash83.6%SourceKimi K381.6%SourceGemini 3.5 Flash leads this result
Blueprint-Bench 2
Gemini 3.5 Flash33.6%SourceKimi K3—Not directly comparable
OfficeQA Pro
Gemini 3.5 Flash—Kimi K363.3%SourceNot directly comparable
MMMU-Pro w/ Python
Gemini 3.5 Flash—Kimi K383.4%SourceNot directly comparable
CharXiv w/o tools
Gemini 3.5 Flash—Kimi K384.8%SourceNot directly comparable
MathVision
Gemini 3.5 Flash—Kimi K394.3%SourceNot directly comparable
MathVision w/ Python
Gemini 3.5 Flash—Kimi K397.8%SourceNot directly comparable
BabyVision w/ Python
Gemini 3.5 Flash—Kimi K385.7%SourceNot directly comparable
ZeroBench
Gemini 3.5 Flash—Kimi K323.0%SourceNot directly comparable
ZeroBench w/ Python
Gemini 3.5 Flash—Kimi K341.0%SourceNot directly comparable
WorldVQA ForceAnswer
Gemini 3.5 Flash—Kimi K351.0%SourceNot directly comparable
OmniDocBench
Gemini 3.5 Flash—Kimi K391.1%SourceNot directly comparable
PerceptionBench
Gemini 3.5 Flash—Kimi K358.5%SourceNot directly comparable
Frequently asked questions
Which is better, Gemini 3.5 Flash or Kimi K3?
Kimi K3 has the higher public score, 80.53 versus 64.69, 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, Gemini 3.5 Flash 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, Gemini 3.5 Flash or Kimi K3?
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, Gemini 3.5 Flash or Kimi K3?
For the stated presets, chat costs $0.006 on Gemini 3.5 Flash and $0.0105 on Kimi K3; repository review costs $0.102 and $0.195; the cache-heavy agent loop costs $0.15 and $0.27. Costs use the listed standard API rates.
Which has the larger context window, Gemini 3.5 Flash 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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