DeepSeek · Open weights
DeepSeek V3.2 Exp
DeepSeek V3.2 Exp is an experimental V3-series model with improved long-context efficiency compared with earlier V3 releases. FP8.
- Input
- Text
- Output
- Text
- Discovery tier
- Open weights
Pricing
USD per 1M tokens- Input
- $0.28
- Output
- $0.42
Reference prices as published by the model provider. API example
Specifications
- Context window
- 163.8K
- Max output
- 65.5K
- Average output (7 days)
- 716 tokens
- Longer than 62% of 468 models
Side by side
DeepSeek V3.2 Exp compared
Specifications, prices, speed and benchmark scores next to each other. Benchmarks below show every compared model too.
| DeepSeek V3.2 ExpDeepSeekThis model | GPT 5.1OpenAIRemove | |
|---|---|---|
| Provider | DeepSeek | OpenAI |
| Discovery tier | Open weights | Frontier |
| Added | Jan 1, 2024 | Nov 13, 2025 |
| Limits | ||
| Context window | 163.84K | 400KBest |
| Max output | 65.54K | 128KBest |
| Average output | 716 tokens | 294 tokens |
| Pricing, USD per 1M tokens | ||
| Input | $0.28Best | $1.25 |
| Output | $0.42Best | $10.00 |
| Cache read | — | $0.13 |
| Performance | ||
| Throughput | 17.9 tok/s | — |
| Time to first token | 3.7 s | — |
| Request success (24h) | 99.8% | 100.0%Best |
| Benchmark indexes | ||
| Intelligence Index | 13.9Best | 13.3 |
| Math Index | 57.7Best | 38.0 |
| Capabilities | ||
| Reasoning | No | Yes |
| Tools | No | Yes |
| Vision | No | Yes |
| Structured output | No | Yes |
| PDF input | No | Yes |
| Reasoning effort | — | none, low, medium, high |
Public evaluations
Benchmarks
Independent evaluation results, with how each score ranks among the models in the Noumen catalog.
- DeepSeek V3.2 Exp
- GPT 5.1
Intelligence Index
- DeepSeek V3.2 Exp13.9
- GPT 5.113.3
DeepSeek V3.2 Exp: Better than 34% of 326 scored models
Indexes
Math Index
Composite of the math evaluations
- DeepSeek V3.2 Exp: 57.7Top
- GPT 5.1: 38.0
Document reasoning
AA-LCRv1.1
Reasoning across long documents
- DeepSeek V3.2 Exp: 44.7%
- GPT 5.1: 45.0%Top
Reasoning and knowledge
Humanity’s Last Exam
Expert-level questions across academic fields
- DeepSeek V3.2 Exp: 9.0%Top
- GPT 5.1: 5.3%
GPQA Diamond
Graduate-level science questions
- DeepSeek V3.2 Exp: 73.8%Top
- GPT 5.1: 64.3%
MMLU-Pro
Multi-subject knowledge and reasoning
- DeepSeek V3.2 Exp: 83.6%Top
- GPT 5.1: 80.1%
IFBench
Following precise output instructions
- DeepSeek V3.2 Exp: 43.1%
- GPT 5.1: 43.2%Top
Coding
LiveCodeBench
Recent competitive programming problems
- DeepSeek V3.2 Exp: 55.4%Top
- GPT 5.1: 49.4%
Math
AIME 2025
Competition mathematics, 2025 problems
- DeepSeek V3.2 Exp: 57.7%Top
- GPT 5.1: 38.0%
Legacy evaluations
Terminal-Bench Hard
Earlier terminal task suite
- DeepSeek V3.2 Exp: 25.0%Top
- GPT 5.1: 22.7%
τ²-Bench Telecom
Tool use in a customer-support simulation
- DeepSeek V3.2 Exp: 33.9%
- GPT 5.1: 46.5%Top
AA-LCR (unversioned)
Long-context reasoning, earlier grading
- DeepSeek V3.2 Exp: 44.7%
- GPT 5.1: 45.0%Top
Scores from Artificial Analysis, updated Oct 26, 2026. Artificial Analysis
- DeepSeek V3.2 Exp
- GPT 5.1
| Leaderboard | DeepSeek V3.2 Exp | GPT 5.1 |
|---|---|---|
| Vision Style Control · Creative Writing | Not in top 20 | #3 · 1284.6 |
| Vision Style Control · Captioning | Not in top 20 | #4 · 1248.2 |
| Vision Style Control · Entity Recognition | Not in top 20 | #11 · 1228.2 |
Ranks among Noumen catalog models on LMArena leaderboards. Only top-20 placements are listed.LMArena
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
- 17.9 tok/s
- Faster than 9% of 261 models
- Time to first token
- 3.7 s
- Quicker than 47% of 261 models
- Prompt cache hits
- 58.2%
- Request success (24h)
- 99.8%
- 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": "deepseek-ai/deepseek-v3.2-exp",
"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="deepseek-ai/deepseek-v3.2-exp",
messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)DeepSeek
Related models
Other DeepSeek models, starting with the same family.