DeepSeek V4-Flash GA: Agent Benchmarks, Responses API, and What Didn't Change
DeepSeek's V4-Flash 2026-07-31 GA: big agent-benchmark gains, native Responses API plus Codex support, and the same architecture as preview. How to read the numbers and what stays on V4-Pro.
On 2026-07-31, DeepSeek moved V4-Flash to its GA API endpoint (announced as a public beta). The release note leads with agent benchmarks that sit well above the V4-Pro-Preview numbers we tracked earlier, plus two integration changes that matter more than the scores: native Responses API support and a Codex-specific adaptation.
The part that should stop you from overreacting: V4-Flash-0731 is the same model size and structure as V4-Flash-preview, only re-post-trained. This is not a new architecture; it is a tuned checkpoint. The other fine print is that only the V4-Flash API changed — V4-Pro API and the APP/WEB models are untouched, and DeepSeek says a V4-Pro GA "will follow soon."
What the announcement actually changed
| Area | Before (preview) | GA (2026-07-31) |
|---|---|---|
| Model ID | deepseek-v4-flash | Same deepseek-v4-flash; deepseek-chat / deepseek-reasoner retired 2026-07-24 |
| Architecture | V4-Flash-preview | Same size and structure, re-trained only |
| Responses API | Not mentioned in GA note | Native support |
| Codex | Generic tool calling | Adapted for Codex |
| V4-Pro API / APP / WEB | Current | Unchanged |
One detail to check on your end: the old aliases deepseek-chat and deepseek-reasoner were scheduled to stop three months after the April V4 launch, around 2026-07-24. If your CI still points at either name, this GA note is your reminder to migrate to the explicit model ID before retries start hitting an error.
The agent benchmark table (read it in two halves)
DeepSeek reports nine scores, and they split into public and internal sets:
| Benchmark | Score | Source |
|---|---|---|
| Terminal Bench 2.1 | 82.7 | Public |
| NL2Repo | 54.2 | Public |
| Cybergym | 76.7 | Public |
| DeepSWE | 54.4 | Public |
| Toolathlon verified | 70.3 | Public |
| Agent Last Exam | 25.2 | Public |
| Automation Bench (Public) | 25.1 | Public |
| DSBench-FullStack | 68.7 | Internal |
| DSBench-Hard | 59.6 | Internal |
DevCove view: The public tasks still ran in the DeepSeek Harness minimal mode (not yet released) at
maxtier,topp=0.95,temperature=1.0. A vendor harness that ships after the score is a warning sign for procurement: match the harness, not the number.
The first seven are reproducible on public sets, so independent verification becomes possible once the harness ships. The last two — DSBench-FullStack (full-stack development) and DSBench-Hard (hard coding-agent problems) — are internal and cannot be checked by outsiders. Treat them as directional, not evidence.
What we will not do with these numbers
- We will not call V4-Flash "the best agent model" from one vendor table; the same rule as Best AI coding models for real projects applies — snapshot date, harness, and task mix first.
- We will not swap a model just because the headline says "far above V4-Pro-Preview." Preview versus GA is an unfair baseline; compare against what you actually run today.
- We will not assume the Codex adaptation is zero-config. DeepSeek's note points to a dedicated Codex setup doc; that is a real configuration step, and it stays outside our ship checklist until we run it ourselves.
Quick way to confirm the GA endpoint
Point a small request at your existing base URL with the explicit model ID (use a placeholder key, never a real one):
curl -s https://api.deepseek.com/chat/completions \
-H "Authorization: Bearer $DEEPSEEK_API_KEY" \
-H "Content-Type: application/json" \
-d '{"model":"deepseek-v4-flash","messages":[{"role":"user","content":"ping"}]}'
If the old deepseek-chat alias now errors while deepseek-v4-flash responds, you are on the GA endpoint. base_url in your SDK config stays unchanged — DeepSeek kept it stable.
Bottom line
The Responses API + Codex support and the post-training-only note are the parts to act on; the benchmark spread is context until a released harness lets you reproduce it. If your team already runs DeepSeek via deepseek-v4-flash, check the Codex doc and move off any retired aliases. If you are on V4-Pro, nothing changed for you yet — wait for the GA note rather than planning a migration today.
Related: AI coding model rankings · Claude Opus 5 tiers · Kimi K3 for coding agents · Verification gates for AI coding agents
Source: DeepSeek API update log, 2026-07-31 (api-docs.deepseek.com/zh-cn/updates); verify against the live page before production.