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 | GPT 6 LunaOpenAIRemove | |
|---|---|---|
| Provider | OpenAI | |
| Discovery tier | Frontier | Efficient |
| Added | Feb 21, 2026 | Sep 22, 2026 |
| Limits | ||
| Context window | 1.05M | 1.05MBest |
| Max output | 65.54K | 128KBest |
| Average output | 1.5K tokens | 120 tokens |
| Pricing, USD per 1M tokens | ||
| Input | $2.00 | $0.10Best |
| Output | $12.00 | $0.50Best |
| Cache read | $0.20 | $0.01Best |
| Cache write | $0.38 | $0.13Best |
| Performance | ||
| Throughput | 24.1 tok/s | 68.2 tok/sBest |
| Time to first token | 3.4 sBest | 4.9 s |
| Request success (24h) | 100.0%Best | 99.9% |
| Benchmark indexes | ||
| Intelligence Index | 29.7 | 29.9Best |
| Coding Index | 68.8 | — |
| Capabilities | ||
| Reasoning | Yes | Yes |
| Tools | Yes | Yes |
| Vision | Yes | Yes |
| Structured output | Yes | Yes |
| PDF input | No | Yes |
| Audio input | Yes | No |
| Video input | Yes | No |
| Reasoning effort | — | none, low, medium, high, xhigh, max |
Public evaluations
Benchmarks
Independent evaluation results, with how each score ranks among the models in the Noumen catalog.
- Gemini 3.1 Pro (Preview High)
- GPT 6 Luna
Intelligence Index
- Gemini 3.1 Pro (Preview High)29.7
- GPT 6 Luna29.9
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
- GPT 6 Luna: —
Agentic work
AutomationBench-AA
Workflow automation, penalized for guardrail violations
- Gemini 3.1 Pro (Preview High): 35.4%
- GPT 6 Luna: 40.5%Top
AutomationBench-AA tasks completed
Workflows finished end to end without a guardrail violation
- Gemini 3.1 Pro (Preview High): 9.4%
- GPT 6 Luna: 10.2%Top
Harvey LAB-AAv1.1
Legal tasks passed in full, with no material hallucination
- Gemini 3.1 Pro (Preview High): 0.0%
- GPT 6 Luna: —
AA-Briefcasev1.1
Agentic knowledge work, rated head to head
- Gemini 3.1 Pro (Preview High): 456 Elo
- GPT 6 Luna: 1,097 EloTop
GDPval-AAv2.1
Economically valuable occupational tasks, rated head to head
- Gemini 3.1 Pro (Preview High): 791 Elo
- GPT 6 Luna: 1,263 EloTop
Document reasoning
GDP.pdf
Professional reasoning over PDF documents, all-pass rate
- Gemini 3.1 Pro (Preview High): 17.8%Top
- GPT 6 Luna: 13.8%
AA-LCRv1.1
Reasoning across long documents
- Gemini 3.1 Pro (Preview High): 82.0%Top
- GPT 6 Luna: 78.3%
MLCR-AA
Long-context reasoning over medical records
- Gemini 3.1 Pro (Preview High): 11.1%
- GPT 6 Luna: 18.3%Top
Reasoning and knowledge
Humanity’s Last Exam
Expert-level questions across academic fields
- Gemini 3.1 Pro (Preview High): 47.0%Top
- GPT 6 Luna: 28.3%
GPQA Diamond
Graduate-level science questions
- Gemini 3.1 Pro (Preview High): 94.1%
- GPT 6 Luna: —
IFBench
Following precise output instructions
- Gemini 3.1 Pro (Preview High): 77.1%
- GPT 6 Luna: —
Coding
Terminal-Benchv4.0
Practical software engineering in a terminal
- Gemini 3.1 Pro (Preview High): 4.0%Top
- GPT 6 Luna: 2.5%
SciCode
Scientific computing in Python
- Gemini 3.1 Pro (Preview High): 58.7%Top
- GPT 6 Luna: 50.9%
Legacy evaluations
Terminal-Bench Hard
Earlier terminal task suite
- Gemini 3.1 Pro (Preview High): 53.8%
- GPT 6 Luna: —
τ²-Bench Telecom
Tool use in a customer-support simulation
- Gemini 3.1 Pro (Preview High): 95.6%
- GPT 6 Luna: —
AA-LCR (unversioned)
Long-context reasoning, earlier grading
- Gemini 3.1 Pro (Preview High): 82.0%Top
- GPT 6 Luna: 78.3%
Scores from Artificial Analysis, updated Oct 26, 2026. Artificial Analysis
- Gemini 3.1 Pro (Preview High)
- GPT 6 Luna
| Leaderboard | Gemini 3.1 Pro (Preview High) | GPT 6 Luna |
|---|---|---|
| ARC-AGI-3 (Default harness) | Not in top 20 | #18 · 0.2% |
Ranks among Noumen catalog models on ARC Prize leaderboards. Only top-20 placements are listed.ARC Prize
- Gemini 3.1 Pro (Preview High)
- GPT 6 Luna
| Leaderboard | Gemini 3.1 Pro (Preview High) | GPT 6 Luna |
|---|---|---|
| SVG | Not in top 20 | #16 · 1250 |
Ranks among Noumen catalog models on Design Arena leaderboards. Only top-20 placements are listed.Design Arena
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
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