deepseek-ai/dflash_qwen3_14b_block7 · 仓库更新
模型仓库动态。仓库创建：2026-06-28T12:31:30.000Z。最后修改：2026-06-28T12:33:22.000Z。仓库修改不等同于模型正式发布。 数据经第三方 Hugging Face 镜像采集，需以原始模型页面复核。
接入 API · 个人 AI 解读连接自己的模型解读资讯，浏览新闻无需配置。
DeepSeek · 深度求索 最新消息
追踪 DeepSeek 模型发布、推理能力、开放 API 与官方更新。
55 条资讯按来源发布或更新时间排序
deepseek-ai/dflash_qwen3_8b_block7 · 仓库更新
模型仓库动态。仓库创建：2026-06-28T12:30:07.000Z。最后修改：2026-06-28T12:31:28.000Z。仓库修改不等同于模型正式发布。 数据经第三方 Hugging Face 镜像采集，需以原始模型页面复核。
deepseek-ai/dflash_qwen3_4b_block7 · 仓库更新
模型仓库动态。仓库创建：2026-06-28T12:29:12.000Z。最后修改：2026-06-28T12:30:04.000Z。仓库修改不等同于模型正式发布。 数据经第三方 Hugging Face 镜像采集，需以原始模型页面复核。
deepseek-ai/dspark_gemma4_12b_block7 · 仓库更新
模型仓库动态。仓库创建：2026-06-28T12:27:36.000Z。最后修改：2026-06-28T12:29:10.000Z。仓库修改不等同于模型正式发布。 数据经第三方 Hugging Face 镜像采集，需以原始模型页面复核。
SGLang 发布: v0.5.14
# Highlights New Model Support: [GLM-5.2](https://docs.sglang.io/cookbook/autoregressive/GLM/GLM-5.2), [LiquidAI LFM2.5](https://docs.sglang.io/cookbook/autoregressive/LiquidAI/LFM2.5), [Kimi-K2.7-Code](https://docs.sglang.io/cookbook/autoregressive/Moonshotai
vLLM 发布: v0.23.0
# vLLM v0.23.0 Release Notes Please note that Minimax M3 is not yet supported in this version. Please follow [vLLM recipe](https://recipes.vllm.ai/MiniMaxAI/MiniMax-M3) for usage guides for M3. ## Highlights This release features 408 commits from 200 contribut
vLLM 发布: v0.22.1
## Highlights This release features 8 commits from 6 contributors (1 new)! v0.22.1 is a patch release on top of v0.22.0 with targeted bug fixes plus a couple of additions: new model support for JetBrains' Mellum v2, zentorch-accelerated quantized linear infere
SGLang 发布: v0.5.12.post1
v0.5.12.post1 is a stability patch on top of v0.5.12. It cherry-picks 12 fixes — primarily for DeepSeek V4 — onto the release branch. # Bug Fixes ## DeepSeek V4 * DSV4-Pro emits garbled text during single-token decode on B200/B300 (fix `deep_gemm` UE8M0 scale-
DeepSeek-V4
来源标注日期：2026-04-24（未提供具体时刻）。 The DeepSeek API now supports V4-Pro and V4-Flash, available via both the OpenAI ChatCompletions interface and the Anthropic interface. To access the new models, the base_url remains unchanged, and the model parameter should be set
DeepSeek-V3.2 DeepSeek-V3.2-Speciale
来源标注日期：2025-12-01（未提供具体时刻）。 Both deepseek-chat and deepseek-reasoner have been upgraded to DeepSeek-V3.2. deepseek-chat corresponds to DeepSeek-V3.2's non-thinking mode deepseek-reasoner corresponds to DeepSeek-V3.2's thinking mode DeepSeek-V3.2-Speciale is se
DeepSeek-V3.2-Exp
来源标注日期：2025-09-29（未提供具体时刻）。 Both deepseek-chat and deepseek-reasoner have been upgraded to DeepSeek-V3.2-Exp. deepseek-chat corresponds to DeepSeek-V3.2-Exp's non-thinking mode deepseek-reasoner corresponds to DeepSeek-V3.2-Exp's thinking mode For more details
DeepSeek-V3.1-Terminus
来源标注日期：2025-09-22（未提供具体时刻）。 Both deepseek-chat and deepseek-reasoner have been upgraded to DeepSeek-V3.1-Terminus. deepseek-chat corresponds to DeepSeek-V3.1-Terminus's non-thinking mode, while deepseek-reasoner corresponds to its thinking mode. This update ma
DeepSeek-V3.1
来源标注日期：2025-08-21（未提供具体时刻）。 Both deepseek-chat and deepseek-reasoner have been upgraded to DeepSeek-V3.1. deepseek-chat corresponds to DeepSeek-V3.1's non-thinking mode, while deepseek-reasoner corresponds to its thinking mode. Key updates in DeepSeek-V3.1: Hy
deepseek-reasoner
来源标注日期：2025-05-28（未提供具体时刻）。 deepseek-reasoner Model Upgraded to DeepSeek-R1-0528: Enhanced Reasoning Capabilities Significant benchmark improvements (Pass@1) AIME 2025: 70.0 → 87.5 (+17.5) GPQA: 71.5 → 81.0 (+9.5) LCB_v6: 63.5 → 73.3 (+9.8) Aider: 57.0 → 71.6
deepseek-chat
来源标注日期：2025-03-24（未提供具体时刻）。 deepseek-chat Model Upgraded to DeepSeek-V3-0324: Enhanced Reasoning Capabilities Significant improvements in benchmark performance: MMLU-Pro: 75.9 → 81.2 (+5.3) GPQA: 59.1 → 68.4 (+9.3) AIME: 39.6 → 59.4 (+19.8) LiveCodeBench: 39.2
deepseek-reasoner
来源标注日期：2025-01-20（未提供具体时刻）。 deepseek-reasoner is our new model DeepSeek-R1. You can invoke DeepSeek-V3 by specifying model='deepseek-reasoner'. For details, please refer to: DeepSeek-R1 Release For guides, please refer to: Thinking Mode
deepseek-chat
来源标注日期：2024-12-26（未提供具体时刻）。 The deepseek-chat model has been upgraded to DeepSeek-V3. The API remains unchanged. You can invoke DeepSeek-V3 by specifying model='deepseek-chat'. For details, please refer to: introducing DeepSeek-V3
deepseek-chat
来源标注日期：2024-12-10（未提供具体时刻）。 The deepseek-chat model has been upgraded to DeepSeek-V2.5-1210, with improvements across various capabilities. Relevant benchmarking results include: Mathematical: Performance on the MATH-500 benchmark has improved from 74.8% to 82
deepseek-coder & deepseek-chat Upgraded to DeepSeek V2.5 Model
来源标注日期：2024-09-05（未提供具体时刻）。 The DeepSeek V2 Chat and DeepSeek Coder V2 models have been merged and upgraded into the new model, DeepSeek V2.5. For backward compatibility, API users can access the new model through either deepseek-coder or deepseek-chat. The ne
API Launches Context Caching on Disk Technology
来源标注日期：2024-08-02（未提供具体时刻）。 The DeepSeek API has innovatively adopted hard disk caching, reducing prices by another order of magnitude. For more details on the update, please refer to the documentation Context Caching is Available 2024/08/02.
New API Features
来源标注日期：2024-07-25（未提供具体时刻）。 Update API /chat/completions JSON Mode Function Calling Chat Prefix Completion（Beta） 8K max_tokens（Beta） New API /completions FIM Completion（Beta） For more details, please check the documentation New API Features 2024/07/25
deepseek-coder
来源标注日期：2024-07-24（未提供具体时刻）。 The deepseek-coder model has been upgraded to DeepSeek-Coder-V2-0724.
deepseek-chat
来源标注日期：2024-06-28（未提供具体时刻）。 The deepseek-chat model has been upgraded to DeepSeek-V2-0628. Model's reasoning capabilities have improved, as shown in relevant benchmarks: Coding: HumanEval Pass@1 79.88% -> 84.76% Mathematics: MATH ACC@1 55.02% -> 71.02% Reasoni
deepseek-coder
来源标注日期：2024-06-14（未提供具体时刻）。 The deepseek-coder model has been upgraded to DeepSeek-Coder-V2-0614, significantly enhancing its coding capabilities. It has reached the level of GPT-4-Turbo-0409 in code generation, code understanding, code debugging, and code com
deepseek-chat
来源标注日期：2024-05-17（未提供具体时刻）。 The deepseek-chat model has been upgraded to DeepSeek-V2-0517. The model has seen a significant improvement in following instructions, with the IFEval Benchmark Prompt-Level accuracy jumping from 63.9% to 77.6%. Additionally, on API