AI KNOWLEDGE DESK

Models · entities · concepts · comparisons · practical tools

GETLLMS.ORG
ModelAI models

DeepSeek V4 Flash

DeepSeek V4 Flash is DeepSeek's fast, lower-cost V4 model. On July 31, 2026, DeepSeek upgraded the `deepseek-v4-flash` API to the re-post-trained `DeepSeek-V4-Flash-0731` version in public beta, kept the request model ID unchanged, and released the official 0731 checkpoint under the MIT License.

Why it matters

The update turns V4 Flash into DeepSeek's clearest coding-agent endpoint: it combines a 1M-token context window, 384K maximum output, tool calling, three reasoning effort levels, native Responses API support, 2,500-request account concurrency, open weights, strong independent evaluation, and pricing far below the current V4 Pro endpoint.

Source-backed summary

DeepSeek's current API and model-card surfaces confirm the public-beta API version, stable request ID, official 0731 checkpoint, MIT license, Codex adaptation, serving paths, and vendor benchmark results. Artificial Analysis adds an independent performance, speed, price, and verbosity view. OpenCode supplies a platform-specific adoption snapshot for the V4 Flash line, while Reddit is used only for questions about task cost, provider stability, local deployment, and Flash-versus-Pro selection.

Primary use cases
  • Run cost-sensitive coding agents through the DeepSeek API.
  • Connect Codex clients to a Responses-compatible DeepSeek endpoint.
  • Build long-context text workflows with function calling or server-side web search.
  • Self-host the official MIT checkpoint with vLLM or SGLang on suitable multi-GPU hardware.
  • Compare Flash and the current V4 Pro 0813 hosted endpoint on the same tasks, budget, and harness.
What changed on July 31

The request model remains `deepseek-v4-flash`, but DeepSeek now identifies the backend version as `DeepSeek-V4-Flash-0731`. The company says it keeps the preview model's architecture and size and changes only post-training. The API remains in public beta, while an official MIT-licensed 0731 checkpoint now supersedes the preview weights. V4 Pro and the DeepSeek App/Web models were not upgraded by the API announcement.

  • Request model ID: `deepseek-v4-flash`.
  • Current API version and official checkpoint: `DeepSeek-V4-Flash-0731`.
  • Release status: official API release in public beta, not an unconditional general-availability claim.
Why attention surged after the 0731 update

The release joined three signals that developers could test immediately: DeepSeek reported a large coding-agent improvement without increasing the model size, Artificial Analysis measured the max-effort model among the leading open-weight models in its class, and existing agent products already exposed the stable V4 Flash endpoint. OpenCode reported V4 Flash as its top model in the latest weekly usage snapshot, but that is platform-specific usage for the V4 Flash line rather than global market share or a clean 0731-only cohort.

  • Artificial Analysis reported an Intelligence Index score of 50 and about 103 output tokens per second for the max-effort model on August 6.
  • OpenCode reported 58% of observed weekly Go usage for V4 Flash in its August 6 snapshot.
  • The stable API model ID and direct availability in coding-agent products reduced migration and trial friction.
Responses API and Codex support

V4 Flash is currently the only DeepSeek model documented for the stateless `/responses` endpoint. It accepts text messages, reasoning items, function calls, function results, and server-side web-search calls, but not image or file inputs. DeepSeek also publishes a Codex provider configuration that uses `wire_api = "responses"` for Codex CLI, the desktop app, and the VS Code extension.

  • Responses conversations are stateless, so clients resend the full conversation history.
  • Reasoning effort maps to low, high, or max behavior; thinking is enabled by default.
  • Function tools and server-side web search are supported; image and file inputs are not.
Current API price and limits

DeepSeek lists regular prices of $0.0028 per 1M cache-hit input tokens, $0.14 per 1M cache-miss input tokens, and $0.28 per 1M output tokens. The model has a 1M-token context window, 384K maximum output, and a 2,500 concurrent-request account limit. Low token prices do not guarantee the lowest task cost: Artificial Analysis found the max-effort model unusually verbose, and community tests report that provider retries or cache misses can erase part of the advantage. DeepSeek has announced a future peak/off-peak policy, but the effective date is still pending an official announcement.

Open weights do not mean lightweight local inference

DeepSeek publishes the official 0731 checkpoint under the MIT License with vLLM and SGLang serving instructions. The model is still large: its official high-performance vLLM example uses a four-GB300 node, so local deployment is primarily a multi-GPU or heavily quantized workflow rather than a routine laptop setup. Choose the hosted API when operational simplicity matters and self-host only when hardware, quantization quality, privacy, or sustained volume justify it.

Treat launch benchmarks as vendor-reported

DeepSeek reports large gains on agent benchmarks, including Terminal Bench 2.1, DeepSWE, Toolathlon verified, and internal DSBench sets. These are vendor-reported results, not independent proof. The public coding-agent runs used an unreleased DeepSeek Harness minimal mode with max effort, top-p 0.95, and temperature 1.0, while two DSBench sets are internal.

DeepSeek V4 Flash FAQ

Common questions about DeepSeek V4 Flash.

Is DeepSeek V4 Flash generally available?+

Not as an unconditional GA release. DeepSeek calls July 31 the official V4 Flash API release, but the same announcement says it is in public beta. Use the stable `deepseek-v4-flash` request ID and keep the beta status in production risk reviews.

Does DeepSeek V4 Flash support the Responses API and Codex?+

Yes. V4 Flash is currently the only DeepSeek model documented for the native `/responses` endpoint, and DeepSeek publishes a Codex provider configuration for the CLI, desktop app, and VS Code extension. The endpoint is stateless, so the client must resend conversation history.

Why did DeepSeek V4 Flash become popular after the 0731 update?+

The 0731 release combined a large vendor-reported coding-agent gain with very low API prices, independent evaluation, a stable request ID, direct coding-agent integrations, and official open weights. That made the model cheap and easy to test in real repositories instead of leaving interest at the benchmark-discussion stage.

Can DeepSeek V4 Flash 0731 run locally?+

Yes, DeepSeek publishes the official 0731 checkpoint under the MIT License with vLLM and SGLang instructions. It is not a lightweight local model: the official high-performance example uses four GB300 GPUs, so most individual users need substantial shared memory, aggressive quantization, or a hosted provider.

Is DeepSeek V4 Flash now better than V4 Pro?+

That is not established for every workload. DeepSeek reports much stronger agent benchmark scores for the updated Flash API, but the July 31 release did not update V4 Pro, some tests use an unreleased harness, and two DSBench sets are internal. Compare both endpoints on the same real tasks, tools, effort, latency, and budget.