DeepSeek V4 Flash Official Release (0731): Agent Benchmarks Jump Past V4 Pro — Live on TokenPAPA
DeepSeek V4 Flash 0731 official release is live: Terminal Bench 82.7, DeepSWE 54.4, native Responses API + Codex support. Same API, same model name — already available on TokenPAPA.
DeepSeek V4 Flash Official Release (0731): Agent Benchmarks Jump Past V4 Pro
On July 31, 2026, DeepSeek officially released DeepSeek-V4-Flash to public beta. The API calling convention is unchanged — set model to deepseek-v4-flash and you get the latest version.
The headline: agent capabilities are dramatically stronger, with benchmark scores that beat DeepSeek-V4-Pro-Preview across the board.
And the good news: TokenPAPA already supports the update. No code changes needed.
What's New in V4 Flash 0731
| Aspect | Detail |
|---|---|
| Release | Official version, public beta |
| Model Name | deepseek-v4-flash (unchanged) |
| Architecture | Same structure/size as V4 Flash Preview |
| Change | Post-training refresh only |
| API | Chat Completions + native Responses API |
| Codex | Specifically adapted ✅ |
DeepSeek-V4-Flash-0731 keeps the same model structure and size as DeepSeek-V4-Flash-Preview — only the post-training was redone. The API interface was upgraded for V4 Flash only; V4 Pro API and APP/WEB models are unchanged, and the V4 Pro official release is coming soon.
Agent Benchmark Scores: Flash Beats Pro-Preview
The official release focuses on agentic coding and tool-use. Here are the published scores:
| Benchmark | V4 Flash (0731) | vs V4 Pro Preview |
|---|---|---|
| Terminal Bench 2.1 | 82.7 | Far ahead ✅ |
| NL2Repo | 54.2 | Far ahead ✅ |
| Cybergym | 76.7 | Far ahead ✅ |
| DeepSWE | 54.4 | Far ahead ✅ |
| Toolathlon (verified) | 70.3 | Far ahead ✅ |
| Agent Last Exam | 25.2 | Far ahead ✅ |
| Automation Bench (Public) | 25.1 | Far ahead ✅ |
| DSBench-FullStack (internal) | 68.7 | Far ahead ✅ |
| DSBench-Hard (internal) | 59.6 | Far ahead ✅ |
Note: For public Code Agent benchmarks, DeepSeek used the DeepSeek Harness minimal mode (upcoming release) with max settings,
top_p=0.95,temperature=1.0. DSBench-FullStack is an internal full-stack dev test set; DSBench-Hard is an internal hard Coding Agent test set.
What this means: for agentic workloads — terminal automation, repo generation, cybersecurity tasks, full-stack development — the Flash tier now delivers flagship-class agent ability at Flash pricing.
What This Means for Developers
- Cheapest agent model just got stronger — V4 Flash was already the budget workhorse ($0.14/1M input, $0.28/1M output, $0.0028/1M cache-hit input). Now its agent skills rival the Pro tier.
- Responses API + Codex ready — native support means you can drop it into modern OpenAI tooling and Codex-style agent loops without translation layers.
- No migration cost — same model name, same endpoint. Existing code keeps working.
- Pro official version incoming — expect the V4 Pro refresh soon; Flash users get the upgrade today.
Try It on TokenPAPA Right Now
TokenPAPA already supports the updated deepseek-v4-flash — same API, same model name:
from openai import OpenAI
client = OpenAI(
api_key="your-tokenpapa-key",
base_url="https://tokenpapa.ai/v1"
)
response = client.chat.completions.create(
model="deepseek-v4-flash", # Latest official version
messages=[{"role": "user", "content": "Write a Python script that scans a repo and summarizes TODO comments."}]
)
print(response.choices[0].message.content)Using the native Responses API
response = client.responses.create(
model="deepseek-v4-flash",
input="List all open issues from this GitHub repo and suggest fixes.",
)
print(response.output_text)Using it with Codex-style tool loops
# TokenPAPA is OpenAI-compatible, so Codex and similar agents work directly:
# 1. Set base_url to https://tokenpapa.ai/v1
# 2. Set model to deepseek-v4-flash
# 3. The agent handles function/tool calls nativelyWhy Access V4 Flash Through TokenPAPA?
- One key, 30+ models — switch between DeepSeek, GPT, Claude, Gemini, Kimi, Qwen, Mimo with a single line change
- No VPN / no Chinese phone required for overseas developers
- OpenAI, Claude, and Gemini native formats all supported
- Instant upgrade — the 0731 release is already live
Getting Started
- Sign up at tokenpapa.ai — free credits on registration
- Get your API key from the console
- Call
deepseek-v4-flash— you're on the latest official version today
from openai import OpenAI
client = OpenAI(base_url="https://tokenpapa.ai/v1", api_key="your-key")
resp = client.chat.completions.create(
model="deepseek-v4-flash",
messages=[{"role": "user", "content": "Explain your agent capabilities in one sentence."}]
)
print(resp.choices[0].message.content)このガイドはいかがですか?
