Google · Frontier
Gemini 3.1 Pro (Preview High)
Gemini 3.1 Pro preview high-reasoning variant.
- Reasoning
- Tools
- Vision
- Structured output
- Audio input
- Video input
- Input
- Text, Images, Video, Audio
- Output
- Text
- Discovery tier
- Frontier
Pricing
USD per 1M tokens- Input
- $2.00
- Output
- $12.00
- Cache read
- $0.20
- Cache write
- $0.38
Reference prices as published by the model provider. API example
Specifications
- Context window
- 1M
- Max output
- 65.5K
- Average output (7 days)
- 1.5K tokens
- Longer than 86% of 465 models
Side by side
Gemini 3.1 Pro (Preview High) compared
Specifications, prices, speed and benchmark scores next to each other. Benchmarks below show every compared model too.
| Gemini 3.1 Pro (Preview High)GoogleThis model | Gemma 4 26B A4B CybersecurityGoogleRemove | |
|---|---|---|
| Provider | ||
| Discovery tier | Frontier | Open weights |
| Added | Feb 21, 2026 | Sep 19, 2026 |
| Limits | ||
| Context window | 1.05MBest | 262.14K |
| Max output | 65.54KBest | 32.77K |
| Average output | 1.5K tokens | 600 tokens |
| Pricing, USD per 1M tokens | ||
| Input | $2.00 | $0.11Best |
| Output | $12.00 | $0.33Best |
| Cache read | $0.20 | $0.0528Best |
| Cache write | $0.38 | — |
| Performance | ||
| Throughput | 24.1 tok/s | — |
| Time to first token | 3.4 s | — |
| Request success (24h) | 100.0%Best | 61.4% |
| Benchmark indexes | ||
| Intelligence Index | 29.7 | — |
| Coding Index | 68.8 | — |
| Capabilities | ||
| Reasoning | Yes | Yes |
| Tools | Yes | Yes |
| Vision | Yes | Yes |
| Structured output | Yes | No |
| Audio input | Yes | No |
| Video input | Yes | No |
| Reasoning effort | — | — |
Public evaluations
Benchmarks
Independent evaluation results, with how each score ranks among the models in the Noumen catalog.
- Gemini 3.1 Pro (Preview High)
- Gemma 4 26B A4B Cybersecurity
Intelligence Index
- Gemini 3.1 Pro (Preview High)29.7
- Gemma 4 26B A4B Cybersecurity—
Gemini 3.1 Pro (Preview High): Better than 71% of 326 scored models
Indexes
Coding Index
Composite of the coding evaluations
- Gemini 3.1 Pro (Preview High): 68.8
- Gemma 4 26B A4B Cybersecurity: —
Agentic work
AutomationBench-AA
Workflow automation, penalized for guardrail violations
- Gemini 3.1 Pro (Preview High): 35.4%
- Gemma 4 26B A4B Cybersecurity: —
AutomationBench-AA tasks completed
Workflows finished end to end without a guardrail violation
- Gemini 3.1 Pro (Preview High): 9.4%
- Gemma 4 26B A4B Cybersecurity: —
Harvey LAB-AAv1.1
Legal tasks passed in full, with no material hallucination
- Gemini 3.1 Pro (Preview High): 0.0%
- Gemma 4 26B A4B Cybersecurity: —
AA-Briefcasev1.1
Agentic knowledge work, rated head to head
- Gemini 3.1 Pro (Preview High): 456 Elo
- Gemma 4 26B A4B Cybersecurity: —
GDPval-AAv2.1
Economically valuable occupational tasks, rated head to head
- Gemini 3.1 Pro (Preview High): 791 Elo
- Gemma 4 26B A4B Cybersecurity: —
Document reasoning
GDP.pdf
Professional reasoning over PDF documents, all-pass rate
- Gemini 3.1 Pro (Preview High): 17.8%
- Gemma 4 26B A4B Cybersecurity: —
AA-LCRv1.1
Reasoning across long documents
- Gemini 3.1 Pro (Preview High): 82.0%
- Gemma 4 26B A4B Cybersecurity: —
MLCR-AA
Long-context reasoning over medical records
- Gemini 3.1 Pro (Preview High): 11.1%
- Gemma 4 26B A4B Cybersecurity: —
Reasoning and knowledge
Humanity’s Last Exam
Expert-level questions across academic fields
- Gemini 3.1 Pro (Preview High): 47.0%
- Gemma 4 26B A4B Cybersecurity: —
GPQA Diamond
Graduate-level science questions
- Gemini 3.1 Pro (Preview High): 94.1%
- Gemma 4 26B A4B Cybersecurity: —
IFBench
Following precise output instructions
- Gemini 3.1 Pro (Preview High): 77.1%
- Gemma 4 26B A4B Cybersecurity: —
Coding
Terminal-Benchv4.0
Practical software engineering in a terminal
- Gemini 3.1 Pro (Preview High): 4.0%
- Gemma 4 26B A4B Cybersecurity: —
SciCode
Scientific computing in Python
- Gemini 3.1 Pro (Preview High): 58.7%
- Gemma 4 26B A4B Cybersecurity: —
Legacy evaluations
Terminal-Bench Hard
Earlier terminal task suite
- Gemini 3.1 Pro (Preview High): 53.8%
- Gemma 4 26B A4B Cybersecurity: —
τ²-Bench Telecom
Tool use in a customer-support simulation
- Gemini 3.1 Pro (Preview High): 95.6%
- Gemma 4 26B A4B Cybersecurity: —
AA-LCR (unversioned)
Long-context reasoning, earlier grading
- Gemini 3.1 Pro (Preview High): 82.0%
- Gemma 4 26B A4B Cybersecurity: —
Scores from Artificial Analysis, updated Oct 26, 2026. Artificial Analysis
Live routing data
Performance and reliability
Recent averages across requests routed for this model. Your own speed depends on prompt length, reasoning effort and load.
- Throughput
- 24.1 tok/s
- Faster than 15% of 250 models
- Time to first token
- 3.4 s
- Quicker than 50% of 250 models
- Prompt cache hits
- 1.1%
- About $1.98 per 1M input tokens with caching
- Request success (24h)
- 100.0%
- Reliable
Cache hits are the share of input tokens recently served from a prompt cache across all requests. They are not a forecast of your own hit rate.
- Healthy (98% or more)
- Degraded (90–98%)
- Down (under 90%)
- No requests
Developers
Use it through the API
Noumen’s API is OpenAI-compatible: any Chat Completions client works with a base URL and a key.
curl https://www.noumen.xyz/api/v1/chat/completions \
-H "Authorization: Bearer $NOUMEN_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "google/gemini-3.1-pro-preview-high",
"messages": [{ "role": "user", "content": "Explain this stack trace." }]
}'import os
from openai import OpenAI
client = OpenAI(base_url="https://www.noumen.xyz/api/v1", api_key=os.environ["NOUMEN_API_KEY"])
reply = client.chat.completions.create(
model="google/gemini-3.1-pro-preview-high",
messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)Related models
Other Google models, starting with the same family.