DeepSeek · Open weights
DeepSeek Chat 0324
DeepSeek V3 0324, DeepSeek's 03 March 2025 V3 model, optimized for general-purpose tasks. Quantized at FP8.
- Tools
- Structured output
- Input
- Text
- Output
- Text
- Discovery tier
- Open weights
Pricing
USD per 1M tokens- Input
- $0.20
- Output
- $0.77
- Cache read
- $0.14
Reference prices as published by the model provider. API example
Specifications
- Context window
- 128K
- Max output
- 8.2K
- Average output (7 days)
- 280 tokens
- Longer than 29% of 465 models
Side by side
DeepSeek Chat 0324 compared
Specifications, prices, speed and benchmark scores next to each other. Benchmarks below show every compared model too.
| DeepSeek Chat 0324DeepSeekThis model | DeepSeek LatestDeepSeekRemove | |
|---|---|---|
| Provider | DeepSeek | DeepSeek |
| Discovery tier | Open weights | Open weights |
| Added | Jan 1, 2024 | May 3, 2026 |
| Limits | ||
| Context window | 128K | 1.05MBest |
| Max output | 8.19K | 384KBest |
| Average output | 280 tokens | — |
| Pricing, USD per 1M tokens | ||
| Input | $0.20Best | $0.23 |
| Output | $0.77 | $0.69Best |
| Cache read | $0.14 | $0.0073Best |
| Performance | ||
| Throughput | 26.5 tok/s | 234.7 tok/sBest |
| Time to first token | 2.7 s | 2.5 sBest |
| Request success (24h) | 99.9%Best | 99.7% |
| Benchmark indexes | ||
| Intelligence Index | 9.7 | 36.0Best |
| Coding Index | 21.2 | 68.8Best |
| Math Index | 41.0 | — |
| Capabilities | ||
| Reasoning | No | Yes |
| Tools | Yes | Yes |
| Structured output | Yes | Yes |
| Reasoning effort | — | none, low, high, max |
Public evaluations
Benchmarks
Independent evaluation results, with how each score ranks among the models in the Noumen catalog.
- DeepSeek Chat 0324
- DeepSeek Latest
Intelligence Index
- DeepSeek Chat 03249.7
- DeepSeek Latest36.0
DeepSeek Chat 0324: Better than 19% of 326 scored models
Indexes
Coding Index
Composite of the coding evaluations
- DeepSeek Chat 0324: 21.2
- DeepSeek Latest: 68.8Top
Math Index
Composite of the math evaluations
- DeepSeek Chat 0324: 41.0
- DeepSeek Latest: —
Agentic work
AutomationBench-AA
Workflow automation, penalized for guardrail violations
- DeepSeek Chat 0324: 0.3%
- DeepSeek Latest: 56.7%Top
AutomationBench-AA tasks completed
Workflows finished end to end without a guardrail violation
- DeepSeek Chat 0324: 0.0%
- DeepSeek Latest: 25.9%Top
AA-Briefcasev1.1
Agentic knowledge work, rated head to head
- DeepSeek Chat 0324: 68 Elo
- DeepSeek Latest: 1,256 EloTop
GDPval-AAv2.1
Economically valuable occupational tasks, rated head to head
- DeepSeek Chat 0324: 69 Elo
- DeepSeek Latest: 1,449 EloTop
Document reasoning
GDP.pdf
Professional reasoning over PDF documents, all-pass rate
- DeepSeek Chat 0324: 1.6%
- DeepSeek Latest: 11.4%Top
AA-LCRv1.1
Reasoning across long documents
- DeepSeek Chat 0324: 40.7%
- DeepSeek Latest: 80.3%Top
Reasoning and knowledge
Humanity’s Last Exam
Expert-level questions across academic fields
- DeepSeek Chat 0324: 4.7%
- DeepSeek Latest: 41.0%Top
GPQA Diamond
Graduate-level science questions
- DeepSeek Chat 0324: 65.5%
- DeepSeek Latest: 92.8%Top
MMLU-Pro
Multi-subject knowledge and reasoning
- DeepSeek Chat 0324: 81.9%
- DeepSeek Latest: —
IFBench
Following precise output instructions
- DeepSeek Chat 0324: 41.0%
- DeepSeek Latest: —
Coding
Terminal-Benchv4.0
Practical software engineering in a terminal
- DeepSeek Chat 0324: 0.0%
- DeepSeek Latest: 14.1%Top
SciCode
Scientific computing in Python
- DeepSeek Chat 0324: 39.0%
- DeepSeek Latest: 51.0%Top
LiveCodeBench
Recent competitive programming problems
- DeepSeek Chat 0324: 40.5%
- DeepSeek Latest: —
Math
AIME 2025
Competition mathematics, 2025 problems
- DeepSeek Chat 0324: 41.0%
- DeepSeek Latest: —
AIME
Competition mathematics
- DeepSeek Chat 0324: 52.0%
- DeepSeek Latest: —
MATH-500
Competition math problems
- DeepSeek Chat 0324: 94.2%
- DeepSeek Latest: —
Legacy evaluations
Terminal-Bench Hard
Earlier terminal task suite
- DeepSeek Chat 0324: 15.2%
- DeepSeek Latest: —
τ²-Bench Telecom
Tool use in a customer-support simulation
- DeepSeek Chat 0324: 47.1%
- DeepSeek Latest: —
AA-LCR (unversioned)
Long-context reasoning, earlier grading
- DeepSeek Chat 0324: 40.7%
- DeepSeek Latest: 80.3%Top
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
- 26.5 tok/s
- Faster than 17% of 251 models
- Time to first token
- 2.7 s
- Quicker than 64% of 251 models
- Prompt cache hits
- 69.7%
- About $0.15 per 1M input tokens with caching
- Request success (24h)
- 99.9%
- 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-v3-0324",
"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-v3-0324",
messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)DeepSeek
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