Agentic
Like-for-like- Gemini 3.1 Pro
- 38.9
- Supported · #121/152
- Grok 4.3
- 26.9
- Supported · #144/152
- Basis
- BenchAlign lane · 6 vs 3 public rows
- Reading
- Gemini 3.1 Pro leads · intervals overlap
Gemini 3.1 Pro vs Grok 4.3
Updated September 10, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.
Decision reading
Gemini 3.1 Pro has the higher public score estimate, 69.95 versus 59.73, but the 90% score intervals overlap. Treat that as a lead, not a settled winner.
7 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.
Share or export
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.
Coding work
Code generation, repair, and software-engineering tasks
Gemini 3.1 Pro
Gemini 3.1 Pro leads on the public coding lane, 46.3 to 33.6, with Supported evidence for both models, although the 90% intervals overlap.
Confidence: limited
Agentic work
Tool use, computer use, and multi-step task completion
Gemini 3.1 Pro
Gemini 3.1 Pro leads on the public agentic lane, 38.9 to 26.9, with Supported evidence for both models, although the 90% intervals overlap.
Confidence: limited
Chat turn cost
1K fresh input + 500 output tokens
Grok 4.3
Grok 4.3 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
Grok 4.3
Grok 4.3 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
Grok 4.3
Grok 4.3 has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Confidence: listed-rates
Long documents
Prompts that approach the documented context limit
No clear pick
The documented context windows are equal.
Confidence: documented
What is actually comparable
Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.
21 Gemini 3.1 Pro only
7 Shared
- Shared results
- 7
- Gemini 3.1 Pro only
- 21
- Grok 4.3 only
- 0
- Like-for-like categories
- 3 / 8
1 category rests on Estimated evidence or different evidence sets. Those rows remain visible for coverage context but do not name a winner.
Category results, on a stated basis
Each row shows the public-lane category score for both models: the BenchAlign 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.
Coding
Like-for-like- Gemini 3.1 Pro
- 46.3
- Supported · #82/151
- Grok 4.3
- 33.6
- Supported · #131/151
- Basis
- BenchAlign lane · 5 vs 2 public rows
- Reading
- Gemini 3.1 Pro leads · intervals overlap
Knowledge
Like-for-like- Gemini 3.1 Pro
- 66.1
- Supported · #21/183
- Grok 4.3
- 57.0
- Supported · #44/183
- Basis
- BenchAlign lane · 6 vs 2 public rows
- Reading
- Gemini 3.1 Pro leads · intervals overlap
Multimodal
Directional only- Gemini 3.1 Pro
- 79.2
- #12/48
- Grok 4.3
- 65.6
- #25/48
- Basis
- Provisional lane · 2 vs 0 weighted rows
- Reading
- Directional only
Reasoning
Not comparable- Gemini 3.1 Pro
- 50.6
- Unranked · 2 rankable rows
- Grok 4.3
- 65.2
- Unranked · 2 rankable rows
- Basis
- Provisional lane · 2 vs 0 weighted rows
- Reading
- Not comparable
Math
Not comparable- Gemini 3.1 Pro
- 54.3
- Unranked · 2 rankable rows
- Grok 4.3
- Not ranked
- Basis
- Provisional lane · 2 vs 0 weighted rows
- Reading
- Not comparable
Multilingual
Not comparable- Gemini 3.1 Pro
- Not ranked
- Grok 4.3
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Instruction following
Not comparable- Gemini 3.1 Pro
- Not ranked
- Grok 4.3
- 94.4
- #2/123
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
| Category | Gemini 3.1 Pro | Grok 4.3 | Basis | Reading |
|---|---|---|---|---|
| Agentic | 38.9Supported · #121/152 | 26.9Supported · #144/152 | Like-for-likeBenchAlign lane · 6 vs 3 public rows | Gemini 3.1 Pro leads · intervals overlap |
| Coding | 46.3Supported · #82/151 | 33.6Supported · #131/151 | Like-for-likeBenchAlign lane · 5 vs 2 public rows | Gemini 3.1 Pro leads · intervals overlap |
| Knowledge | 66.1Supported · #21/183 | 57.0Supported · #44/183 | Like-for-likeBenchAlign lane · 6 vs 2 public rows | Gemini 3.1 Pro leads · intervals overlap |
| Multimodal | 79.2#12/48 | 65.6#25/48 | Directional onlyProvisional lane · 2 vs 0 weighted rows | Directional only |
| Reasoning | 50.6Unranked · 2 rankable rows | 65.2Unranked · 2 rankable rows | Not comparableProvisional lane · 2 vs 0 weighted rows | Not comparable |
| Math | 54.3Unranked · 2 rankable rows | Not ranked | Not comparableProvisional lane · 2 vs 0 weighted rows | Not comparable |
| Multilingual | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Instruction following | Not ranked | 94.4#2/123 | 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) differ from the provisional-lane categories. Unranked scores sit on the lane’s scale but never name a winner. Like-for-like rows within 0.5 points read as a practical tie.
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.
MMLU-Pro (Vals)
Knowledge
LiveCodeBench (Vals)
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
- Gemini 3.1 Pro
- $0.008
- Fits in one request
- Grok 4.3
- $0.0025
- Fits in one request
Grok 4.3 has the lower modeled cost
Costs use the listed standard API rates.
Repository review
50K fresh input + 3K output tokens
- Gemini 3.1 Pro
- $0.136
- Fits in one request
- Grok 4.3
- $0.07
- Fits in one request
Grok 4.3 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 3.1 Pro
- $0.2
- Fits in one request
- Grok 4.3
- $0.09
- Fits in one request
Grok 4.3 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 3.1 ProGrok 4.3
Context window
Maximum documented context; output-token limits may be lower.
Gemini 3.1 Pro
Grok 4.3
1M
API model ID
Gemini 3.1 Pro
gemini-3.1-pro-preview
Google Gemini 3.1 Pro Preview model documentationGrok 4.3
Not sourced
Cached-input rate
A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.
Gemini 3.1 Pro
$0.2 per 1M cached input tokens
Google Gemini API pricingGrok 4.3
$0.2 per 1M cached input tokens
Documented inputs
Gemini 3.1 Pro
text, image, video, audio, pdf
Google Gemini 3.1 Pro Preview model documentationGrok 4.3
Not sourced
Documented outputs
Gemini 3.1 Pro
Grok 4.3
Not sourced
Provider availability
Gemini 3.1 Pro
Preview · Gemini API, Google AI Studio
Google Gemini model catalogGrok 4.3
Not sourced
Reasoning profile
Gemini 3.1 Pro
Reasoning
Grok 4.3
Reasoning
Weight access
Gemini 3.1 Pro
Proprietary
Grok 4.3
Proprietary
License
Gemini 3.1 Pro
Proprietary
Grok 4.3
Proprietary
Release date
Gemini 3.1 Pro
2026-02-19
Grok 4.3
2026-04-30
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
- Gemini 3.1 Pro has the higher public score estimate, 69.95 versus 59.73, but the 90% score intervals overlap.
- Workload cost
- Repository review: $0.136 vs $0.07. Cache-heavy agent loop: $0.2 vs $0.09.
- Context tradeoff
- Both models list 1M.
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 evidence28 rows
Agentic
Claw-Eval
Gemini 3.1 Pro57.8%SourceGrok 4.3—Not directly comparable
DeepSearchQA
Gemini 3.1 Pro69.7%SourceGrok 4.3—Not directly comparable
τ²-bench results
Gemini 3.1 Pro95.6%SourceGrok 4.3—Not directly comparable
Gert Labs
Shared sourceGemini 3.1 Pro56.87%Grok 4.343.86%Gemini 3.1 Pro leads this result
ResearchClawBench
Shared sourceGemini 3.1 Pro13.3%Grok 4.312.4%Gemini 3.1 Pro leads this result
Terminal-Bench 2.1 (Vals)
Gemini 3.1 Pro70.8%SourceGrok 4.341.9%SourceGemini 3.1 Pro leads this result
Coding
LiveCodeBench Pro
Gemini 3.1 Pro82.9%SourceGrok 4.3—Not directly comparable
React Native Evals
Gemini 3.1 Pro78.9%SourceGrok 4.3—Not directly comparable
Vibe Code Bench
Gemini 3.1 Pro32.03%SourceGrok 4.3—Not directly comparable
LiveCodeBench (Vals)
Gemini 3.1 Pro88.5%SourceGrok 4.384.5%SourceGemini 3.1 Pro leads this result
SWE-bench (Vals)
Gemini 3.1 Pro78.8%SourceGrok 4.371.4%SourceGemini 3.1 Pro leads this result
Reasoning
Knowledge
GPQA-D
Gemini 3.1 Pro94.3%SourceGrok 4.3—Not directly comparable
HLE w/o tools
Gemini 3.1 Pro45.4%SourceGrok 4.3—Not directly comparable
HealthBench Hard
Gemini 3.1 Pro20.6%SourceGrok 4.3—Not directly comparable
MedXpertQA (Text)
Gemini 3.1 Pro71.5%SourceGrok 4.3—Not directly comparable
GPQA Diamond (Vals)
Gemini 3.1 Pro95.5%SourceGrok 4.391.4%SourceGemini 3.1 Pro leads this result
MMLU-Pro (Vals)
Gemini 3.1 Pro91.0%SourceGrok 4.385.8%SourceGemini 3.1 Pro leads this result
Math
Multimodal
MMMU-Pro
Gemini 3.1 Pro83.9%SourceGrok 4.3—Not directly comparable
CharXiv
Gemini 3.1 Pro80.2%SourceGrok 4.3—Not directly comparable
ERQA
Gemini 3.1 Pro69.4%SourceGrok 4.3—Not directly comparable
SimpleVQA
Gemini 3.1 Pro72.4%SourceGrok 4.3—Not directly comparable
ScreenSpot Pro
Gemini 3.1 Pro84.4%SourceGrok 4.3—Not directly comparable
ZeroBench
Gemini 3.1 Pro29.0%SourceGrok 4.3—Not directly comparable
MedXpertQA (MM)
Gemini 3.1 Pro81.3%SourceGrok 4.3—Not directly comparable
Frequently asked questions
Which is better, Gemini 3.1 Pro or Grok 4.3?
Gemini 3.1 Pro has the higher public score estimate, 69.95 versus 59.73, but the 90% score intervals overlap. The higher estimate is not a decisive winner because the uncertainty ranges overlap.
Which is better for coding, Gemini 3.1 Pro or Grok 4.3?
Gemini 3.1 Pro leads the public coding lane, 46.3 to 33.6, with Supported evidence for both models, although the 90% intervals overlap.
Which is better for agentic tasks, Gemini 3.1 Pro or Grok 4.3?
Gemini 3.1 Pro leads the public agentic tasks lane, 38.9 to 26.9, with Supported evidence for both models, although the 90% intervals overlap.
Which costs less, Gemini 3.1 Pro or Grok 4.3?
For the stated presets, chat costs $0.008 on Gemini 3.1 Pro and $0.0025 on Grok 4.3; repository review costs $0.136 and $0.07; the cache-heavy agent loop costs $0.2 and $0.09. Costs use the listed standard API rates.
Which has the larger context window, Gemini 3.1 Pro or Grok 4.3?
Both models list the same context window, 1M.
Related comparisons
Last updated September 10, 2026
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