Hugging Face에서 DeepSeek V4.1 Flash 발견
확인됨가중치 공개근거 링크 22개
영어 원문

DeepSeek
Default deepseek-v4.1-flash with four fallbacks; RPM 6, budget 200.
paid model; the cheap tier (deepseek-v4.1-flash, glm-5.3-flash, qwen3.8-flash,
ollama-cloud, model deepseek-v4.1-flash (previously nous). The host
500,000 tokens, the output limit to the 393,216 DeepSeek-V4.1-Flash reports, and a tool result to 131,072 characters. The step and tool-call histograms reach past their
- Switch that run to `deepseek/deepseek-v4.1-flash` once the main agent is idle when the team has an active Token Pass, without saving it as the
against the Python frontend side by side on DeepSeek-V4.1-Flash (both frontends TP2 EP2 on one GB300 tray); the remaining differences are pre-existing main-vs-branch gaps or
against the Python frontend side by side on DeepSeek-V4.1-Flash (both frontends TP2 EP2 on one GB300 tray); the remaining differences are pre-existing main-vs-branch gaps or
against the Python frontend side by side on DeepSeek-V4.1-Flash (both frontends TP2 EP2 on one GB300 tray); the remaining differences are pre-existing main-vs-branch gaps or
against the Python frontend side by side on DeepSeek-V4.1-Flash (both frontends TP2 EP2 on one GB300 tray); the remaining differences are pre-existing main-vs-branch gaps or
against the Python frontend side by side on DeepSeek-V4.1-Flash (both frontends TP2 EP2 on one GB300 tray); the remaining differences are pre-existing main-vs-branch gaps or
against the Python frontend side by side on DeepSeek-V4.1-Flash (both frontends TP2 EP2 on one GB300 tray); the remaining differences are pre-existing main-vs-branch gaps or
against the Python frontend side by side on DeepSeek-V4.1-Flash (both frontends TP2 EP2 on one GB300 tray); the remaining differences are pre-existing main-vs-branch gaps or
against the Python frontend side by side on DeepSeek-V4.1-Flash (both frontends TP2 EP2 on one GB300 tray); the remaining differences are pre-existing main-vs-branch gaps or
against the Python frontend side by side on DeepSeek-V4.1-Flash (both frontends TP2 EP2 on one GB300 tray); the remaining differences are pre-existing main-vs-branch gaps or
against the Python frontend side by side on DeepSeek-V4.1-Flash (both frontends TP2 EP2 on one GB300 tray); the remaining differences are pre-existing main-vs-branch gaps or
against the Python frontend side by side on DeepSeek-V4.1-Flash (both frontends TP2 EP2 on one GB300 tray); the remaining differences are pre-existing main-vs-branch gaps or
against the Python frontend side by side on DeepSeek-V4.1-Flash (both frontends TP2 EP2 on one GB300 tray); the remaining differences are pre-existing main-vs-branch gaps or
against the Python frontend side by side on DeepSeek-V4.1-Flash (both frontends TP2 EP2 on one GB300 tray); the remaining differences are pre-existing main-vs-branch gaps or
against the Python frontend side by side on DeepSeek-V4.1-Flash (both frontends TP2 EP2 on one GB300 tray); the remaining differences are pre-existing main-vs-branch gaps or
against the Python frontend side by side on DeepSeek-V4.1-Flash (both frontends TP2 EP2 on one GB300 tray); the remaining differences are pre-existing main-vs-branch gaps or
1_048_576), so a single turn reserved **$1.2156** on `deepseek/deepseek-v4.1-flash`. `admit()` refuses when `spent + reserved + estimate > cap`, so once a period's headroom fell
claude-opus-5-5; claude-sonnet-5-5; gpt-6.1-sol (via OMP; reported as openai-codex/gpt-6.1-sol); opencode-go/deepseek-v4.1-flash (via OMP; canonical id not exposed)
**Campaigns** (model `deepseek-v4.1-flash`, envelope 2,200 requests / 18M input / 1M output / 8h):
`AgentEndpoint` runs a tool-calling assistant on OpenCode Zen (`deepseek-v4.1-flash`) or the user's own OpenAI-compatible provider, metered at published prices against the included allowance. Bring-your-own keys
Created with DeepSeek V4.1 Flash 1017 in OpenCode. The CVE scanner was written by a poteto-agent subagent on the same model.
wally partition, because the model ids name vendors (`wally/deepseek-v4.1-flash` would otherwise be claimed by deepseek).
the last 30 days included about 15k unpriced `deepseek-v4.1-flash` attempts across four relays. There were also `gemini-4-argon` on Vertex/Cursor/Zed, `cn:`-prefixed Kimi/GLM/MiniMax/Step ids, and `zd/`-prefixed relay
usage limit; resets unknown`, and `opencode run -m opencode-go/deepseek-v4.1-flash` printed `Insufficient balance. Top up at https://opencode.ai/console/wrk_01M28N93AE612R8VKHHW47PJER/billing?credits=1`. The login is restored (`opencode models --standalone` lists the
first-line review round 2: 2 findings (recorded: model deepseek/deepseek-v4.1-flash, at 2f1878d) · review levels: level 1: changes in round 2 on `2f1878d` · model cost
first-line review round 1: 3 findings (recorded: model deepseek/deepseek-v4.1-flash, at 13904df) · tests failed on `13904df` · model cost $0.14 of $10 cap · updated
model="deepinfra/deepseek-ai/DeepSeek-V4.1-Flash", # DeepInfra honours the vLLM option
the identical gate model + rubric (nous / deepseek-v4.1-flash) run with the endpoint timeout extended to 300s. No revision rounds used.
security fixes, one run per case, same model (DeepSeek-V4.1-Flash), sanitized repos. Baseline = the current phase ladder; new = fused pre-RED + fused resolution. Complexity
returning a module. W38 and W39 use fresh DeepSeek-V4.1-Flash generations. W38 selected a signed-int16 table, but counted column chunks for a row slab and chose
- Model(s) used: `deepseek-v4.1-flash` (Magpie provider)
- Model(s) used: deepseek-v4.1-flash - Tool(s) used: Codex CLI via T3 Code harness
- Model(s) used: GPT-5 via Codex, deepseek-v4.1-flash. - Tool(s) used: Codex/T3 Code and DeepSeek implementation/review workers.
- Model(s) used: GPT-5 via Codex, deepseek-v4.1-flash. - Tool(s) used: Codex/T3 Code and DeepSeek implementation/review workers.
(model DeepSeek-V4.1-Flash).
- DeepSeek V4.1 Flash: catalog entries, the model table row and its section of the DeepSeek V4 page.
API changes DeepSeek V4.1 Flash is now available on the DeepSeek API with native multimodal support
Right now, you can test 5 models for free in Cline: Gemini 3.8 Flash MiniMax M3.1 👀 MiMo-V2.6-Flash DeepSeek V4.1 Flash Muse Spark 1.3
🚨 DeepSeek V4.1 Flash is out • New architecture: it only uses the part of the model it actually needs, making it faster and cheaper. • New KV cache: long conversations and agent workflows are noticeably cheaper to run. • On coding and agent tasks, it’s already close to Opus 5 and GPT-5.6 Sol. • And all of that at 15x lower cost.
DeepSeek V4.1 Flash: DeepSeek의 AI 모델, 가중치 공개, 출시일 2026-09-10. 컨텍스트 윈도는 1,048,576 토큰입니다.
컨텍스트 윈도는 1,048,576 토큰입니다.
네. DeepSeek에서 가중치를 공개합니다.
2026-09-10.