DeepSeek-V4-Flash-0731
Official DeepSeek-V4-Flash release with enhanced agentic capabilities and 1M-token context.
DeepSeek-V4-Flash-0731 is the official 2026-07-31 release of DeepSeek-V4-Flash, superseding the preview version with enhanced agentic capabilities while keeping the same architecture and size as the preview. It is served through DeepSeek's API as model ID deepseek-v4-flash and published as open weights on Hugging Face.
Pricing
Official page says prices are per 1M tokens and billing is based on total input/output tokens. Input price recorded is cache-miss price; cached input price recorded separately. DeepSeek notes pricing may increase in the near future and recommends checking the page for current pricing.
DeepSeek's official API pricing page lists model version DeepSeek-V4-Flash-0731 under model deepseek-v4-flash, with prices explicitly stated per 1M tokens: cache-hit input $0.0028, cache-miss input $0.14, and output $0.28.
Model Intelligence
Recent stories
OpenCode’s thdxr said Go users spent $1.14 per day on DeepSeek V4 Flash last week. Wafer added a fast OpenRouter route, while Nous extended a 90% discount for the 0731 model.
Together says two V4 Flash attempts solved more DeepSWE tasks than one GPT-5.6 Luna attempt for roughly one-third the cost. Practitioners report Flash-0731 results vary sharply by harness and pass count.
Baseten and Together AI added DeepSeek V4 Flash with a 1M-token context window, reasoning-effort controls, and DSpark decoding. ValsAI ranked it the cheapest model above 60 on its index, and Nous promoted a short 90% discount.
Cline tripled its free quota while Nous discounted Flash 0731 by 90% for a week and OpenHands offered free cloud use. OpenCode reported 8T Flash tokens on Aug. 1.
New tests showed DeepSeek V4 Flash as cheaper per token and faster on some serving paths. Ramp said it cost 3x more than GPT-5.6 Luna per SWE-Bench task because it used more turns.
DeepSeek released V4 Flash 0731 with weights, a technical report, API access, 1M context, MoE routing, and low token prices. Its cited benchmarks show gains on Artificial Analysis, Terminal-Bench, Frontend Code Arena, and agent tests.