DeepSeek · Open weights
DeepSeek V4 Flash 0423
The original 0423 checkpoint of DeepSeek V4 Flash, with a 1M-token context window, text input, tool calling, structured output, and optional reasoning.
- Reasoning
- Tools
- Structured output
- Input
- Text
- Output
- Text
- Reasoning effort
- none · low · high · max
- Discovery tier
- Open weights
Pricing
USD per 1M tokens- Input
- $0.14
- Output
- $0.28
- Cache read
- $0.028
Reference prices as published by the model provider. API example
Specifications
- Context window
- 1M
- Max output
- —
- Average output (7 days)
- 245 tokens
- Longer than 26% of 465 models
Side by side
DeepSeek V4 Flash 0423 compared
Specifications, prices, speed and benchmark scores next to each other. Benchmarks below show every compared model too.
| DeepSeek V4 Flash 0423DeepSeekThis model | GPT 5.4OpenAIRemove | |
|---|---|---|
| Provider | DeepSeek | OpenAI |
| Discovery tier | Open weights | Frontier |
| Added | Oct 7, 2026 | Mar 5, 2026 |
| Limits | ||
| Context window | 1.05M | 1.05MBest |
| Max output | — | 128K |
| Average output | 245 tokens | 409 tokens |
| Pricing, USD per 1M tokens | ||
| Input | $0.14Best | $2.50 |
| Output | $0.28Best | $15.00 |
| Cache read | $0.028Best | $0.25 |
| Performance | ||
| Throughput | 131.1 tok/s | — |
| Time to first token | 2.0 s | — |
| Request success (24h) | 98.3% | 100.0%Best |
| Benchmark indexes | ||
| Intelligence Index | 18.9Best | 18.2 |
| Capabilities | ||
| Reasoning | Yes | Yes |
| Tools | Yes | Yes |
| Vision | No | Yes |
| Structured output | Yes | Yes |
| PDF input | No | Yes |
| Reasoning effort | none, low, high, max | none, low, medium, high, xhigh |
Public evaluations
Benchmarks
Independent evaluation results, with how each score ranks among the models in the Noumen catalog.
- DeepSeek V4 Flash 0423
- GPT 5.4
Intelligence Index
- DeepSeek V4 Flash 042318.9
- GPT 5.418.2
DeepSeek V4 Flash 0423: Better than 48% of 326 scored models
Document reasoning
AA-LCRv1.1
Reasoning across long documents
- DeepSeek V4 Flash 0423: 41.7%
- GPT 5.4: 58.3%Top
Reasoning and knowledge
Humanity’s Last Exam
Expert-level questions across academic fields
- DeepSeek V4 Flash 0423: 7.8%
- GPT 5.4: 11.3%Top
GPQA Diamond
Graduate-level science questions
- DeepSeek V4 Flash 0423: 71.6%
- GPT 5.4: 74.8%Top
IFBench
Following precise output instructions
- DeepSeek V4 Flash 0423: 47.2%
- GPT 5.4: 48.4%Top
Legacy evaluations
Terminal-Bench Hard
Earlier terminal task suite
- DeepSeek V4 Flash 0423: 34.1%
- GPT 5.4: 37.9%Top
τ²-Bench Telecom
Tool use in a customer-support simulation
- DeepSeek V4 Flash 0423: 94.4%Top
- GPT 5.4: 36.0%
AA-LCR (unversioned)
Long-context reasoning, earlier grading
- DeepSeek V4 Flash 0423: 41.7%
- GPT 5.4: 58.3%Top
Scores from Artificial Analysis, updated Oct 26, 2026. Artificial Analysis
- DeepSeek V4 Flash 0423
- GPT 5.4
| Leaderboard | DeepSeek V4 Flash 0423 | GPT 5.4 |
|---|---|---|
| Roleplay | Not in top 20 | #17 · 19.9% |
Ranks among Noumen catalog models on Use cases leaderboards. Only top-20 placements are listed.
- DeepSeek V4 Flash 0423
- GPT 5.4
| Leaderboard | DeepSeek V4 Flash 0423 | GPT 5.4 |
|---|---|---|
| Industry Mathematical | Not in top 20 | #19 · 1499.0 |
| Japanese | Not in top 20 | #14 · 1480.2 |
| Multi Turn | Not in top 20 | #14 · 1492.9 |
| Vision Style Control Overall | Not in top 20 | #16 · 1284.1 |
| Vision Style Control · Diagram | Not in top 20 | #11 · 1321.0 |
| Vision Style Control · English | Not in top 20 | #12 · 1280.9 |
| Vision Style Control · Homework | Not in top 20 | #10 · 1329.8 |
| Vision Style Control · Ocr | Not in top 20 | #16 · 1298.8 |
| Search Overall | Not in top 20 | #15 · 1199.1 |
| Document Overall | Not in top 20 | #11 · 1471.0 |
| Document Style Control Overall | Not in top 20 | #14 · 1470.1 |
Ranks among Noumen catalog models on LMArena leaderboards. Only top-20 placements are listed.LMArena
- DeepSeek V4 Flash 0423
- GPT 5.4
| Leaderboard | DeepSeek V4 Flash 0423 | GPT 5.4 |
|---|---|---|
| Epoch Capabilities Index | Not in top 20 | #14 · 159.6 |
| FrontierMath v2 (Tiers 1–3) | Not in top 20 | #2 · 82.5% |
| SWE-bench Verified | Not in top 20 | #4 · 76.9% |
| GPQA Diamond | Not in top 20 | #1 · 94.6% |
Ranks among Noumen catalog models on Epoch AI leaderboards. Only top-20 placements are listed.Epoch AI
- DeepSeek V4 Flash 0423
- GPT 5.4
| Leaderboard | DeepSeek V4 Flash 0423 | GPT 5.4 |
|---|---|---|
| ARC-AGI-1 | Not in top 20 | #18 · 94.5% |
| ARC-AGI-2 | Not in top 20 | #15 · 83.3% |
| ARC-AGI-3 (Default harness) | Not in top 20 | #17 · 0.2% |
Ranks among Noumen catalog models on ARC Prize leaderboards. Only top-20 placements are listed.ARC Prize
- DeepSeek V4 Flash 0423
- GPT 5.4
| Leaderboard | DeepSeek V4 Flash 0423 | GPT 5.4 |
|---|---|---|
| EQ-Bench 4 | Not in top 20 | #9 · 1260 |
| EQ-Bench 3 | Not in top 20 | #14 · 1537 |
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
- 131.1 tok/s
- Faster than 72% of 250 models
- Time to first token
- 2.0 s
- Quicker than 78% of 250 models
- Prompt cache hits
- 92.6%
- About $0.0363 per 1M input tokens with caching
- Request success (24h)
- 98.4%
- 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/deepseek-v4-flash-0423",
"reasoning_effort": "none",
"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/deepseek-v4-flash-0423",
messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)DeepSeek
Related models
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