Coding work
Code generation, repair, and software-engineering tasks
Not enough matched evidence
Gemini 3 Pro Deep Think is not ranked on the public lane for coding, so no winner is named for coding.
Confidence: limited
Gemini 3 Pro Deep Think vs Kimi K3
Updated October 2, 2026. We do not rank this pair: at least one has no public score. Public scores include evidence status and uncertainty.
Both of these models will change. Get the price, version and retirement notices for the pair, each with its source. Follow model changes
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Decision reading
At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner. 1 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.
- Shared results
- 1
- Gemini 3 Pro Deep Think only
- 0
- Kimi K3 only
- 47
- Like-for-like categories
- 0 / 8
Supported: Kimi K3How the comparison works
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.
No workload recommendation clears the current evidence threshold.
Use the matched evidence, workload costs, and sourced specifications below instead of treating a point score as a universal answer.
Show secondary and unsupported calls
Agentic work
Tool use, computer use, and multi-step task completion
Not enough matched evidence
Gemini 3 Pro Deep Think is not ranked on the public lane for agentic, so no winner is named for agentic.
Confidence: limitedLong documents
Prompts that approach the documented context limit
Not enough matched evidence
A complete context comparison is not sourced.
Confidence: limitedChat turn cost
1K fresh input + 500 output tokens
Not enough matched evidence
A complete comparable API-rate estimate is not available for both models.
Confidence: listed-ratesCache-heavy agent loop cost
200K cached + 20K fresh input + 10K output tokens
Not enough matched evidence
A complete comparable API-rate estimate is not available for both models.
Confidence: listed-ratesRepository review cost
50K fresh input + 3K output tokens
Not enough matched evidence
A complete comparable API-rate estimate is not available for both models.
Confidence: listed-rates
Which one for a specific job
Choose a job from the LLM Selector's task catalog to see the category row it rests on, under the same basis rules as the table below. A directional row stays directional; choosing a job never creates a winner.
The same task catalog as the LLM Selector. Each job names the evidence surface it rests on; nothing here adds a new score.
—Gemini 3 Pro Deep Think61.4Kimi K3
Not comparable · BenchAlign v5.8
The coding row is not comparable on the public lane: at least one model is not measured or not ranked there.
Coding scores combine specific tasks and setups. Match the editor, harness, and effort to your workflow.
Same basis rules as the category table below
What is actually comparable
Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.
1 Shared
47 Kimi K3 only
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.
ARC-AGI-2Reasoning
Normalized gap 15.3Gemini 3 Pro Deep Think:45.1%Kimi K3:60.4%
Bars run 0–100 on each benchmark’s normalized display scale
Category results, on a stated basis
Each row shows the public-lane category score for both models: the BenchAlign v5.8 lane for agentic, coding, and knowledge, and the weighted public rows elsewhere, with the same rank each model page reports. A row is like-for-like only when both scores rest on Supported evidence or the same weighted set. Directional and not-comparable rows remain visible, but they never receive a winner.
Agentic
Not comparable- Gemini 3 Pro Deep Think
- Not ranked
- Kimi K3
- 68.1
- Supported · #8/119
- Basis
- BenchAlign v5.8 lane · 0 vs 12 public rows
- Reading
- Not comparable
Coding
Not comparable- Gemini 3 Pro Deep Think
- Not ranked
- Kimi K3
- 61.4
- Supported · #18/144
- Basis
- BenchAlign v5.8 lane · 0 vs 14 public rows
- Reading
- Not comparable
Reasoning
Not comparable- Gemini 3 Pro Deep Think
- 44.1
- Unranked · 1 rankable row
- Kimi K3
- 65.8
- #18/27
- Basis
- Provisional lane · 1 vs 1 weighted rows
- Reading
- Not comparable
Multimodal
Not comparable- Gemini 3 Pro Deep Think
- Not ranked
- Kimi K3
- 89.4
- #1/49
- Basis
- Provisional lane · 0 vs 3 weighted rows
- Reading
- Not comparable
Knowledge
Not comparable- Gemini 3 Pro Deep Think
- Not ranked
- Kimi K3
- 67.9
- Supported · #18/171
- Basis
- BenchAlign v5.8 lane · 0 vs 6 public rows
- Reading
- Not comparable
Multilingual
Not comparable- Gemini 3 Pro Deep Think
- Not ranked
- Kimi K3
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Instruction following
Not comparable- Gemini 3 Pro Deep Think
- Not ranked
- Kimi K3
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Math
Not comparable- Gemini 3 Pro Deep Think
- Not ranked
- Kimi K3
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
| Category | Gemini 3 Pro Deep Think | Kimi K3 | Basis | Reading |
|---|---|---|---|---|
| Agentic | Not ranked | 68.1Supported · #8/119 | Not comparableBenchAlign v5.8 lane · 0 vs 12 public rows | Not comparable |
| Coding | Not ranked | 61.4Supported · #18/144 | Not comparableBenchAlign v5.8 lane · 0 vs 14 public rows | Not comparable |
| Reasoning | 44.1Unranked · 1 rankable row | 65.8#18/27 | Not comparableProvisional lane · 1 vs 1 weighted rows | Not comparable |
| Multimodal | Not ranked | 89.4#1/49 | Not comparableProvisional lane · 0 vs 3 weighted rows | Not comparable |
| Knowledge | Not ranked | 67.9Supported · #18/171 | Not comparableBenchAlign v5.8 lane · 0 vs 6 public rows | Not comparable |
| Multilingual | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Instruction following | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Math | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
Ranks count the models scored in each category’s lane, so the agentic, coding, and knowledge denominators (BenchAlign v5.8) differ from the provisional-lane categories. Unranked scores sit on the provisional lane’s scale but never name a winner. Like-for-like rows within 0.5 points read as a practical tie.
Supported evidence per lane · bars run 0–100Methodology
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 Pro Deep Think
- API rate not published
- Fit state unavailable
- Kimi K3
- $0.0105
- Fits in one request
Gemini 3 Pro Deep Think has no comparable published API token rate.
Repository review
50K fresh input + 3K output tokens
- Gemini 3 Pro Deep Think
- API rate not published
- Fit state unavailable
- Kimi K3
- $0.195
- Fits in one request
Gemini 3 Pro Deep Think has no comparable published API token rate.
Cache-heavy agent loop
200K cached + 20K fresh input + 10K output tokens
- Gemini 3 Pro Deep Think
- API rate not published
- Fit state unavailable
- Cached-input rate unavailable
- Kimi K3
- $0.27
- Fits in one request
Gemini 3 Pro Deep Think has no comparable published API token rate.
Cached input falls back to the list input rate only where a cached rate is unpublished
Specification differences
Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.
SpecificationGemini 3 Pro Deep ThinkKimi K3
Context window
Maximum documented context; output-token limits may be lower.
Gemini 3 Pro Deep Think
Not sourced
Google Gemini 3 Deep Think launchKimi K3
1.05M
API model ID
Gemini 3 Pro Deep Think
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.
Gemini 3 Pro Deep Think
No comparable hosted API rate
Kimi K3
$0.3 per 1M cached input tokens
Documented inputs
Gemini 3 Pro Deep Think
Not sourced
Kimi K3
Not sourced
Documented outputs
Gemini 3 Pro Deep Think
Not sourced
Kimi K3
Not sourced
Provider availability
Gemini 3 Pro Deep Think
Limited Access · Gemini app for Google AI Ultra, Gemini API early-access program
Google Gemini 3 Deep Think launchKimi K3
Not sourced
Reasoning profile
Gemini 3 Pro Deep Think
Reasoning
Kimi K3
Reasoning
Weight access
Gemini 3 Pro Deep Think
Proprietary
Kimi K3
Pending
License
Gemini 3 Pro Deep Think
Proprietary
Kimi K3
Pending
Release date
Gemini 3 Pro Deep Think
2026-02-12
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
- 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
- A complete comparable API-rate estimate is not available for both models.
- Context tradeoff
- A complete documented context comparison is not available.
Run the same representative tasks against both endpoints before changing production traffic.
Questions
Which is better, Gemini 3 Pro Deep Think or Kimi K3?
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, Gemini 3 Pro Deep Think or Kimi K3?
Gemini 3 Pro Deep Think is not ranked on the public lane for coding, so no winner is named for coding.
Which is better for agentic tasks, Gemini 3 Pro Deep Think or Kimi K3?
Gemini 3 Pro Deep Think is not ranked on the public lane for agentic tasks, so no winner is named for agentic tasks.
Which costs less, Gemini 3 Pro Deep Think or Kimi K3?
Both models do not have comparable published API token rates, so this page does not name a universal price winner.
Which has the larger context window, Gemini 3 Pro Deep Think or Kimi K3?
A complete documented context-window comparison is not available.
Benchmark evidence
The full public result ledger is available for audit without forcing a wide desktop table onto a phone.
Browse raw public benchmark evidence48 rows
Agentic
Terminal-Bench 2.1
Gemini 3 Pro Deep Think—Kimi K388.3%SourceNot directly comparable
BrowseComp
Gemini 3 Pro Deep Think—Kimi K391.2%SourceNot directly comparable
DeepSearchQA
Gemini 3 Pro Deep Think—Kimi K395.0%SourceNot directly comparable
Toolathlon-Verified
Gemini 3 Pro Deep Think—Kimi K373.2%SourceNot directly comparable
MCP Atlas
Gemini 3 Pro Deep Think—Kimi K384.2%SourceNot directly comparable
AutomationBench
Gemini 3 Pro Deep Think—Kimi K330.8%SourceNot directly comparable
JobBench
Gemini 3 Pro Deep Think—Kimi K352.9%SourceNot directly comparable
APEX-Agents
Gemini 3 Pro Deep Think—Kimi K337.6%SourceNot directly comparable
SpreadsheetBench 2
Gemini 3 Pro Deep Think—Kimi K334.8%SourceNot directly comparable
DECK-Bench
Gemini 3 Pro Deep Think—Kimi K373.5%SourceNot directly comparable
Terminal-Bench 2.1 (Vals)
Gemini 3 Pro Deep Think—Kimi K380.9%SourceNot directly comparable
ApprenticeBench
Gemini 3 Pro Deep Think—Kimi K318%SourceNot directly comparable
Coding
DeepSWE
Gemini 3 Pro Deep Think—Kimi K367.5%SourceNot directly comparable
CursorBench 3.2
Gemini 3 Pro Deep Think—Kimi K360.8%SourceNot directly comparable
FrontierSWE
Gemini 3 Pro Deep Think—Kimi K381.2%SourceNot directly comparable
ProgramBench
Gemini 3 Pro Deep Think—Kimi K377.8%SourceNot directly comparable
Kimi Code Bench v2
Gemini 3 Pro Deep Think—Kimi K372.9%SourceNot directly comparable
sweMarathon
Gemini 3 Pro Deep Think—Kimi K342%SourceNot directly comparable
PostTrain Bench
Gemini 3 Pro Deep Think—Kimi K336.6%SourceNot directly comparable
MLS-Bench Lite
Gemini 3 Pro Deep Think—Kimi K348.3%SourceNot directly comparable
VulcanBench v3
Gemini 3 Pro Deep Think—Kimi K373.7%SourceNot directly comparable
OpenHarmony Bench
Gemini 3 Pro Deep Think—Kimi K357.3%SourceNot directly comparable
FrontierSWE v2
Gemini 3 Pro Deep Think—Kimi K325.9%SourceNot directly comparable
LiveCodeBench (Vals)
Gemini 3 Pro Deep Think—Kimi K387.2%SourceNot directly comparable
SWE-bench (Vals)
Gemini 3 Pro Deep Think—Kimi K393.4%SourceNot directly comparable
PostTrainBench v1.1
Gemini 3 Pro Deep Think—Kimi K332.0%SourceNot directly comparable
Reasoning
Multimodal
OfficeQA Pro
Gemini 3 Pro Deep Think—Kimi K363.3%SourceNot directly comparable
MMMU-Pro
Gemini 3 Pro Deep Think—Kimi K381.6%SourceNot directly comparable
MMMU-Pro w/ Python
Gemini 3 Pro Deep Think—Kimi K383.4%SourceNot directly comparable
CharXiv w/o tools
Gemini 3 Pro Deep Think—Kimi K384.8%SourceNot directly comparable
CharXiv
Gemini 3 Pro Deep Think—Kimi K391.3%SourceNot directly comparable
MathVision
Gemini 3 Pro Deep Think—Kimi K394.3%SourceNot directly comparable
MathVision w/ Python
Gemini 3 Pro Deep Think—Kimi K397.8%SourceNot directly comparable
BabyVision w/ Python
Gemini 3 Pro Deep Think—Kimi K385.7%SourceNot directly comparable
ZeroBench
Gemini 3 Pro Deep Think—Kimi K323.0%SourceNot directly comparable
ZeroBench w/ Python
Gemini 3 Pro Deep Think—Kimi K341.0%SourceNot directly comparable
WorldVQA ForceAnswer
Gemini 3 Pro Deep Think—Kimi K351.0%SourceNot directly comparable
OmniDocBench
Gemini 3 Pro Deep Think—Kimi K391.1%SourceNot directly comparable
PerceptionBench
Gemini 3 Pro Deep Think—Kimi K358.5%SourceNot directly comparable
Knowledge
GPQA
Gemini 3 Pro Deep Think—Kimi K393.5%SourceNot directly comparable
GPQA-D
Gemini 3 Pro Deep Think—Kimi K393.5%SourceNot directly comparable
HLE
Gemini 3 Pro Deep Think—Kimi K356%SourceNot directly comparable
HLE w/o tools
Gemini 3 Pro Deep Think—Kimi K343.5%SourceNot directly comparable
GPQA Diamond (Vals)
Gemini 3 Pro Deep Think—Kimi K392.9%SourceNot directly comparable
MMLU-Pro (Vals)
Gemini 3 Pro Deep Think—Kimi K388.0%SourceNot directly comparable
Instruction following
Gray Swan IPI (15 attempts)
Gemini 3 Pro Deep Think—Kimi K352.7%SourceNot directly comparable
48 public results · 1 shared
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Last updated October 2, 2026