Google · Open weights
Gemma 4 31B Scarlet
Scarlet is a multimodal Gemma 4 31B creative finetune for expressive dialogue, long-form storytelling, and roleplay.
- Reasoning
- Tools
- Vision
- Input
- Text, Images
- Output
- Text
- Discovery tier
- Open weights
Pricing
USD per 1M tokens- Input
- $0.10
- Output
- $0.45
- Cache read
- $0.05
Reference prices as published by the model provider. API example
Specifications
- Context window
- 262.1K
- Max output
- 32.8K
- Average output (7 days)
- 456 tokens
- Longer than 45% of 473 models
Side by side
Gemma 4 31B Scarlet compared
Specifications, prices, speed and benchmark scores next to each other. Benchmarks below show every compared model too.
| Gemma 4 31B ScarletGoogleThis model | LFM2.5 2.6BliquidRemove | |
|---|---|---|
| Provider | liquid | |
| Discovery tier | Open weights | Open weights |
| Added | Oct 8, 2026 | Aug 12, 2026 |
| Limits | ||
| Context window | 262.14KBest | 128K |
| Max output | 32.77K | 32.77K |
| Average output | 456 tokens | 459 tokens |
| Pricing, USD per 1M tokens | ||
| Input | $0.10 | $0.10 |
| Output | $0.45 | $0.20Best |
| Cache read | $0.05 | — |
| Performance | ||
| Throughput | 15.5 tok/s | — |
| Time to first token | 8.5 s | — |
| Request success (24h) | 94.1% | — |
| Benchmark indexes | ||
| Intelligence Index | — | 8.4 |
| Coding Index | — | 7.7 |
| Capabilities | ||
| Reasoning | Yes | Yes |
| Tools | Yes | Yes |
| Vision | Yes | No |
| Structured output | No | Yes |
| Reasoning effort | — | minimal, low, medium, high, xhigh |
Public evaluations
Benchmarks
Independent evaluation results, with how each score ranks among the models in the Noumen catalog.
- Gemma 4 31B Scarlet
- LFM2.5 2.6B
Intelligence Index
- Gemma 4 31B Scarlet—
- LFM2.5 2.6B8.4
Indexes
Coding Index
Composite of the coding evaluations
- Gemma 4 31B Scarlet: —
- LFM2.5 2.6B: 7.7
Document reasoning
AA-LCRv1.1
Reasoning across long documents
- Gemma 4 31B Scarlet: —
- LFM2.5 2.6B: 5.7%
Reasoning and knowledge
Humanity’s Last Exam
Expert-level questions across academic fields
- Gemma 4 31B Scarlet: —
- LFM2.5 2.6B: 6.2%
GPQA Diamond
Graduate-level science questions
- Gemma 4 31B Scarlet: —
- LFM2.5 2.6B: 55.8%
Coding
SciCode
Scientific computing in Python
- Gemma 4 31B Scarlet: —
- LFM2.5 2.6B: 14.4%
Legacy evaluations
AA-LCR (unversioned)
Long-context reasoning, earlier grading
- Gemma 4 31B Scarlet: —
- LFM2.5 2.6B: 5.7%
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
- 15.5 tok/s
- Faster than 5% of 256 models
- Time to first token
- 8.5 s
- Quicker than 11% of 256 models
- Prompt cache hits
- 6.0%
- About $0.097 per 1M input tokens with caching
- Request success (24h)
- 94.1%
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.
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": "gemma-4-31b-it-scarlet",
"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="gemma-4-31b-it-scarlet",
messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)Related models
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