Multimodal
Directional only- Gemini 3.1 Pro
- 82.6
- Interfaze Beta
- 71.1
- Weighted basis
- 2 vs 1 rows
- Reading
- Directional only
Model comparison
Gemini 3.1 Pro vs Interfaze Beta
Updated August 10, 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.
2 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.
Chat turn cost
1K fresh input + 500 output tokens
Interfaze Beta
Interfaze Beta 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 3.1 Pro
Gemini 3.1 Pro has the lower estimated token cost for this stated workload. Interfaze Beta has no published cached-input rate, so cached tokens use its listed input rate.
Confidence: rate-fallback
Show secondary and unsupported calls
Repository review cost
50K fresh input + 3K output tokens
Interfaze Beta
Interfaze Beta 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
No shared weighted benchmark basis supports a winner.
Confidence: limited
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
2 Shared
7 Interfaze Beta only
- Shared results
- 2
- Gemini 3.1 Pro only
- 21
- Interfaze Beta only
- 7
- Like-for-like categories
- 0 / 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.
Agentic
Not comparable- Gemini 3.1 Pro
- Not measured
- Interfaze Beta
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
Coding
Not comparable- Gemini 3.1 Pro
- Not measured
- Interfaze Beta
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
Reasoning
Not comparable- Gemini 3.1 Pro
- 77.1
- Interfaze Beta
- Not measured
- Weighted basis
- 1 vs 0 rows
- Reading
- Not comparable
Knowledge
Not comparable- Gemini 3.1 Pro
- Not measured
- Interfaze Beta
- 89.9
- Weighted basis
- 0 vs 1 rows
- Reading
- Not comparable
Math
Not comparable- Gemini 3.1 Pro
- 31.8
- Interfaze Beta
- Not measured
- Weighted basis
- 2 vs 0 rows
- Reading
- Not comparable
Multilingual
Not comparable- Gemini 3.1 Pro
- Not measured
- Interfaze Beta
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
Instruction following
Not comparable- Gemini 3.1 Pro
- Not measured
- Interfaze Beta
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
| Category | Gemini 3.1 Pro | Interfaze Beta | Weighted basis | Reading |
|---|---|---|---|---|
| Multimodal | 82.6 | 71.1 | Directional only2 vs 1 rows | Directional only |
| Agentic | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
| Coding | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
| Reasoning | 77.1 | Not measured | Not comparable1 vs 0 rows | Not comparable |
| Knowledge | Not measured | 89.9 | Not comparable0 vs 1 rows | Not comparable |
| Math | 31.8 | 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.
MMMU-Pro
Multimodal
Gemini 3.1 Pro: 83.9%Interfaze Beta: 71.1%Normalized gap 12.8Gemini 3.1 Pro source Interfaze Beta source
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
- Interfaze Beta
- $0.00325
- Fits in one request
Interfaze Beta 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
- Interfaze Beta
- $0.0855
- Fits in one request
Interfaze Beta 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
- Interfaze Beta
- $0.365
- Fits in one request
- Cached input priced at the published list-input rate
Gemini 3.1 Pro has the lower modeled cost
Interfaze Beta has no published cached-input rate, so cached tokens use its listed input rate.
Specification differences
Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.
SpecificationGemini 3.1 ProInterfaze Beta
Context window
Maximum documented context; output-token limits may be lower.
Gemini 3.1 Pro
Interfaze Beta
1M
API model ID
Gemini 3.1 Pro
gemini-3.1-pro-preview
Google Gemini 3.1 Pro Preview model documentationInterfaze Beta
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 pricingInterfaze Beta
Not published
Documented inputs
Gemini 3.1 Pro
text, image, video, audio, pdf
Google Gemini 3.1 Pro Preview model documentationInterfaze Beta
Not sourced
Documented outputs
Gemini 3.1 Pro
Interfaze Beta
Not sourced
Provider availability
Gemini 3.1 Pro
Preview · Gemini API, Google AI Studio
Google Gemini model catalogInterfaze Beta
Not sourced
Reasoning profile
Gemini 3.1 Pro
Reasoning
Interfaze Beta
Reasoning
Weight access
Gemini 3.1 Pro
Proprietary
Interfaze Beta
Proprietary
License
Gemini 3.1 Pro
Proprietary
Interfaze Beta
Proprietary
Release date
Gemini 3.1 Pro
2026-02-19
Interfaze Beta
2026-05-11
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
- Repository review: $0.136 vs $0.0855. Cache-heavy agent loop: $0.2 vs $0.365.
- 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 evidence30 rows
Agentic
Claw-Eval
Gemini 3.1 Pro57.8%SourceInterfaze Beta—Not directly comparable
DeepSearchQA
Gemini 3.1 Pro69.7%SourceInterfaze Beta—Not directly comparable
τ²-bench results
Gemini 3.1 Pro95.6%SourceInterfaze Beta—Not directly comparable
Gert Labs
Gemini 3.1 Pro56.87%SourceInterfaze Beta—Not directly comparable
ResearchClawBench
Gemini 3.1 Pro13.3%SourceInterfaze Beta—Not directly comparable
Coding
LiveCodeBench Pro
Gemini 3.1 Pro82.9%SourceInterfaze Beta—Not directly comparable
React Native Evals
Gemini 3.1 Pro78.9%SourceInterfaze Beta—Not directly comparable
Vibe Code Bench
Gemini 3.1 Pro32.03%SourceInterfaze Beta—Not directly comparable
Spider 2.0-Lite
Gemini 3.1 Pro—Interfaze Beta52.9%SourceNot directly comparable
Reasoning
Knowledge
GPQA-D
Gemini 3.1 Pro94.3%SourceInterfaze Beta89.9%SourceGemini 3.1 Pro leads this result
HLE w/o tools
Gemini 3.1 Pro45.4%SourceInterfaze Beta—Not directly comparable
HealthBench Hard
Gemini 3.1 Pro20.6%SourceInterfaze Beta—Not directly comparable
MedXpertQA (Text)
Gemini 3.1 Pro71.5%SourceInterfaze Beta—Not directly comparable
GPQA
Gemini 3.1 Pro—Interfaze Beta89.9%SourceNot directly comparable
MMMLU
Gemini 3.1 Pro—Interfaze Beta90.9%SourceNot directly comparable
Math
Multimodal
MMMU-Pro
Gemini 3.1 Pro83.9%SourceInterfaze Beta71.1%SourceGemini 3.1 Pro leads this result
CharXiv
Gemini 3.1 Pro80.2%SourceInterfaze Beta—Not directly comparable
ERQA
Gemini 3.1 Pro69.4%SourceInterfaze Beta—Not directly comparable
SimpleVQA
Gemini 3.1 Pro72.4%SourceInterfaze Beta—Not directly comparable
ScreenSpot Pro
Gemini 3.1 Pro84.4%SourceInterfaze Beta—Not directly comparable
ZeroBench
Gemini 3.1 Pro29.0%SourceInterfaze Beta—Not directly comparable
MedXpertQA (MM)
Gemini 3.1 Pro81.3%SourceInterfaze Beta—Not directly comparable
OCRBench V2
Gemini 3.1 Pro—Interfaze Beta70.7%SourceNot directly comparable
olmOCR
Gemini 3.1 Pro—Interfaze Beta85.7%SourceNot directly comparable
RefCOCO (avg)
Gemini 3.1 Pro—Interfaze Beta82.1%SourceNot directly comparable
Instruction following
SOB Value Acc
Gemini 3.1 Pro—Interfaze Beta79.5%SourceNot directly comparable
Frequently asked questions
Which is better, Gemini 3.1 Pro or Interfaze Beta?
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 3.1 Pro or Interfaze Beta?
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 3.1 Pro or Interfaze Beta?
The published evidence does not provide a shared weighted agentic tasks basis for both models, so BenchLM does not name a agentic tasks winner.
Which costs less, Gemini 3.1 Pro or Interfaze Beta?
For the stated presets, chat costs $0.008 on Gemini 3.1 Pro and $0.00325 on Interfaze Beta; repository review costs $0.136 and $0.0855; the cache-heavy agent loop costs $0.2 and $0.365. Interfaze Beta has no published cached-input rate, so cached tokens use its listed input rate.
Which has the larger context window, Gemini 3.1 Pro or Interfaze Beta?
Both models list the same context window, 1M.
Related comparisons
Last updated August 10, 2026
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