By DeepSeek made V4 Flash official on July 31, and the buried headline is this: the smaller model now beats the larger one. V4-Flash-0731 outperforms V4-Pro-Preview across all nine published agentic benchmarks — according to DeepSeek’s own release notes. Terminal Bench 2.1 sits at 82.7 for Flash versus Pro’s 72.1. DeepSWE lands at 54.4 versus 12.8. Cybergym: 76.7 versus 52.7. The smaller model wins every category, at a third of the output cost. If you’re running coding agents and haven’t switched yet, here’s your migration guide.
What Changed From Preview to GA
Almost nothing architectural changed — and that’s the interesting part. DeepSeek re-ran only the post-training phase. Same 284B MoE architecture, same 13B active parameters per token, same 1M context window. The model string stays deepseek-v4-flash, so existing integrations require no code changes. What did land in this build: native Responses API support, which makes it directly compatible with Codex-based integrations out of the box.
One housekeeping note before setup: if you’re still calling deepseek-chat or deepseek-reasoner, those aliases retired on July 24. Switch to deepseek-v4-flash now or your calls are failing silently.
The Benchmark Numbers Worth Knowing
| Benchmark | Flash-0731 | Flash Preview | Pro Preview |
|---|---|---|---|
| Terminal Bench 2.1 | 82.7 | 61.8 | 72.1 |
| DeepSWE | 54.4 | 7.3 | 12.8 |
| Cybergym | 76.7 | 38.7 | 52.7 |
| NL2Repo | 54.2 | 39.4 | 38.5 |
| Toolathlon (verified) | 70.3 | 49.7 | 55.9 |
On DeepSWE — a real-world software engineering benchmark — Flash is more than four times better than its preview version and four times better than Pro Preview. Independent verification from Artificial Analysis puts Flash at #2 of 162 models measured. One developer in the HackerNews discussion put it plainly: “It would absolutely have been a frontier model last December.”
What It Costs — Honestly
| Token Type | V4-Flash | V4-Pro |
|---|---|---|
| Input (cache miss) | $0.14/M | $0.435/M |
| Input (cache hit) | $0.0028/M | $0.003625/M |
| Output | $0.28/M | $0.87/M |
Output tokens cost 3x less than Pro. Cache hits knock 98% off input costs — critical for agentic loops where your system prompt repeats on every tool call. In practice, a full day of agent-heavy work runs under $0.50 on Flash versus roughly $2 on Pro.
There’s a real caveat here: Flash generates approximately three times the median token volume on agentic tasks due to its internal reasoning chain. Effective cost per completed task runs higher than raw rates suggest — but it’s still cheaper than Pro in every real-world scenario. Also worth noting: DeepSeek has announced a 2x peak-hour surcharge during Beijing business hours, effective date still TBD.
Setting Up in Claude Code
DeepSeek provides an Anthropic-compatible endpoint, so setup is a handful of environment variables. The official integration docs cover it, but the smart mapping is to assign Flash to lighter slots (Haiku, subagents) and Pro to the main model role:
export ANTHROPIC_BASE_URL=https://api.deepseek.com/anthropic
export ANTHROPIC_AUTH_TOKEN=your_deepseek_api_key
export ANTHROPIC_MODEL=deepseek-v4-pro
export ANTHROPIC_DEFAULT_OPUS_MODEL=deepseek-v4-pro
export ANTHROPIC_DEFAULT_SONNET_MODEL=deepseek-v4-pro
export ANTHROPIC_DEFAULT_HAIKU_MODEL=deepseek-v4-flash
export CLAUDE_CODE_SUBAGENT_MODEL=deepseek-v4-flash
export CLAUDE_CODE_EFFORT_LEVEL=max
export CLAUDE_CODE_AUTO_COMPACT_WINDOW=786432This maps Flash to the high-frequency sub-tasks and reserves Pro for the primary reasoning pass. Given that Flash outperforms Pro on every agentic benchmark, you could map everything to Flash — but the hybrid approach is the sensible starting point while Pro’s GA is still pending.
Setting Up in Cursor
Open Settings (Cmd+, on Mac, Ctrl+, on Windows), go to Models, and toggle “Override OpenAI Base URL.” Enter https://api.deepseek.com — no trailing /v1. Paste your DeepSeek API key into the OpenAI key field, click “+ Add model,” type deepseek-v4-flash, and hit Verify. Switch to it in the chat model picker before starting a session.
There’s one important caveat here: Cursor’s Composer panel has a known issue with extended tool-call sequences. Cursor only forwards the content field to the model — not reasoning_content — which causes failures when DeepSeek’s thinking mode needs to replay its chain across multiple requests. Use the Chat panel for complex multi-step tasks or disable thinking mode for Composer sessions. Background Agents also don’t support custom models as of this writing.
Get Your API Key
If you don’t have one, start at the DeepSeek platform. Minimum wallet funding is $5 — that covers weeks of normal agent usage at Flash pricing.
The Takeaway
V4-Flash is the agent model of summer 2026. A frontier-adjacent model at sub-commodity pricing, MIT-licensed, open weights available for self-hosting on 4x A100s. V4-Pro still hasn’t hit GA — when it does, the picture may shift. For now, Flash is the default choice for coding agents. The benchmarks say so, and so does your wallet.
