DeepSeek · Open weights
DeepSeek V4.1 Flash TEE
DeepSeek V4.1 Flash's October 17, 2026 checkpoint (1017) supports text and image input, reasoning, tool calling, and structured output with a 1M-token context window. This route runs through Tinfoil attested inference inside a Trusted Execution Environment. Tinfoil lists this model as experimental, with availability subject to change.
- Reasoning
- Tools
- Vision
- Structured output
- Parallel tools
- Input
- Text, Images
- Output
- Text
- Reasoning effort
- none · low · medium · high · max
- Discovery tier
- Open weights
Pricing
USD per 1M tokens- Input
- $0.65
- Output
- $1.45
- Cache read
- $0.13
Reference prices as published by the model provider. API example
Specifications
- Context window
- 1M
- Max output
- 384K
- Average output (7 days)
- 571 tokens
- Longer than 53% of 465 models
Side by side
DeepSeek V4.1 Flash TEE compared
Specifications, prices, speed and benchmark scores next to each other. Benchmarks below show every compared model too.
| DeepSeek V4.1 Flash TEEDeepSeekThis model | InklingthinkingmachinesRemove | |
|---|---|---|
| Provider | DeepSeek | thinkingmachines |
| Discovery tier | Open weights | Open weights |
| Added | Sep 12, 2026 | Jul 15, 2026 |
| Limits | ||
| Context window | 1.05MBest | 1.05M |
| Max output | 384KBest | 32.77K |
| Average output | 571 tokens | 596 tokens |
| Pricing, USD per 1M tokens | ||
| Input | $0.65Best | $1.00 |
| Output | $1.45Best | $4.05 |
| Cache read | $0.13Best | $0.17 |
| Performance | ||
| Throughput | 239.9 tok/s | — |
| Time to first token | 3.0 s | — |
| Request success (24h) | 99.9% | 100.0%Best |
| Benchmark indexes | ||
| Intelligence Index | 24.7 | 25.0Best |
| Coding Index | — | 52.1 |
| Capabilities | ||
| Reasoning | Yes | No |
| Tools | Yes | Yes |
| Vision | Yes | Yes |
| Structured output | Yes | Yes |
| Audio input | No | Yes |
| Parallel tools | Yes | No |
| Reasoning effort | none, low, medium, high, max | — |
Public evaluations
Benchmarks
Independent evaluation results, with how each score ranks among the models in the Noumen catalog.
- DeepSeek V4.1 Flash TEE
- Inkling
Intelligence Index
- DeepSeek V4.1 Flash TEE24.7
- Inkling25.0
DeepSeek V4.1 Flash TEE: Better than 60% of 326 scored models
Indexes
Coding Index
Composite of the coding evaluations
- DeepSeek V4.1 Flash TEE: —
- Inkling: 52.1
Agentic work
AutomationBench-AA
Workflow automation, penalized for guardrail violations
- DeepSeek V4.1 Flash TEE: 47.8%Top
- Inkling: 5.0%
AutomationBench-AA tasks completed
Workflows finished end to end without a guardrail violation
- DeepSeek V4.1 Flash TEE: 14.2%Top
- Inkling: 0.3%
Harvey LAB-AAv1.1
Legal tasks passed in full, with no material hallucination
- DeepSeek V4.1 Flash TEE: —
- Inkling: 0.0%
AA-Briefcasev1.1
Agentic knowledge work, rated head to head
- DeepSeek V4.1 Flash TEE: 1,118 EloTop
- Inkling: 832 Elo
GDPval-AAv2.1
Economically valuable occupational tasks, rated head to head
- DeepSeek V4.1 Flash TEE: 1,340 EloTop
- Inkling: 1,072 Elo
Document reasoning
GDP.pdf
Professional reasoning over PDF documents, all-pass rate
- DeepSeek V4.1 Flash TEE: 3.8%
- Inkling: 12.8%Top
AA-LCRv1.1
Reasoning across long documents
- DeepSeek V4.1 Flash TEE: 55.3%
- Inkling: 77.3%Top
MLCR-AA
Long-context reasoning over medical records
- DeepSeek V4.1 Flash TEE: —
- Inkling: 6.1%
Reasoning and knowledge
Humanity’s Last Exam
Expert-level questions across academic fields
- DeepSeek V4.1 Flash TEE: 10.8%
- Inkling: 31.9%Top
GPQA Diamond
Graduate-level science questions
- DeepSeek V4.1 Flash TEE: —
- Inkling: 87.2%
Coding
Terminal-Benchv4.0
Practical software engineering in a terminal
- DeepSeek V4.1 Flash TEE: 5.6%Top
- Inkling: 1.0%
SciCode
Scientific computing in Python
- DeepSeek V4.1 Flash TEE: 35.5%
- Inkling: 47.0%Top
Legacy evaluations
AA-LCR (unversioned)
Long-context reasoning, earlier grading
- DeepSeek V4.1 Flash TEE: 55.3%
- Inkling: 77.3%Top
Scores from Artificial Analysis, updated Oct 26, 2026. Artificial Analysis
- DeepSeek V4.1 Flash TEE
- Inkling
| Leaderboard | DeepSeek V4.1 Flash TEE | Inkling |
|---|---|---|
| EQ-Bench 4 | Not in top 20 | #15 · 1216 |
Ranks among Noumen catalog models on EQ-Bench leaderboards. Only top-20 placements are listed.EQ-Bench
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
- 239.9 tok/s
- Faster than 88% of 250 models
- Time to first token
- 3.0 s
- Quicker than 57% of 250 models
- Prompt cache hits
- 69.7%
- About $0.29 per 1M input tokens with caching
- Request success (24h)
- 99.5%
- 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": "TEE/deepseek-v4.1-flash",
"reasoning_effort": "medium",
"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="TEE/deepseek-v4.1-flash",
messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)DeepSeek
Related models
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