Alex Getmanearly AI signals

DeepSeek R1

DeepSeek

Released Updated
Context window
64K
64,000 tokens

Timeline

  1. · Weights version · evidence link
  1. · Evidence links · GitHub search · DeepSeek · commits · warejohn4366/war · @warejohn4366
    Excerpt
    随着AI发展,企业和开发者希望快速应用AI模型。本文介绍在阿里云PAI Model Gallery上零代码一键部署DeepSeek-V3和DeepSeek-R1模型的方法,包括准备工作、部署步骤、调用方式等。这种方式简化流程、提高效率、降低成本,助力AI能力落地。
  2. · Evidence links · GitHub search · DeepSeek · pulls · overnightworks/speech · @dependabot[bot]
    Excerpt
    XTX, <a href="https://redirect.github.com/vllm-project/vllm/issues/59774">#59774</a>); and gfx1250 enablement for gpt-oss-120b, DeepSeek-R1, DeepSeek-V4-Flash and MiniMax-M3 (<a href="https://redirect.github.com/vllm-project/vllm/issues/58800">#58800</a>).</li>
  3. · Evidence links · GitHub search · DeepSeek · pulls · anomalyco/models.dev · @models-dev-automation[bot]
    Excerpt
    Instruct-Turbo`, `openai/gpt-oss-120b-Turbo`, `google/gemma-4-31B-it-Ultra`, `mattshumer/Reflection-Llama-3.1-70B`, `NovaSky-AI/Sky-T1-32B-Preview`, `deepseek-ai/DeepSeek-R1`, `Qwen/Qwen2-7B-Instruct`, `Qwen/QwQ-32B`, `google/gemma-2-9b-it`, `google/gemma-4-31B-it-turbo`, `Qwen/Qwen3.5-0.8B`, `deepseek-ai/DeepSeek-V3-0324-Turbo`, `openbmb/MiniCPM-Llama3-V-2_5`, `microsoft/phi-4`, `inclusionAI/Ling-3.0-flash-VL`, `Qwen/Qwen3-VL-30B-A3B-Thinking`, `MiniMaxAI/MiniMax-M2.7-Turbo`, `deepseek-ai
  4. · Evidence links · GitHub search · DeepSeek · pulls · ROCm/aiter · @karverma-amd
    Excerpt
    Tuned configs for DeepSeek-R1 MLA-absorb bmms (B=128). Previously fell back to DEFAULT (untuned): 5.5x slower at decode M~1536 . Lets the BF16 MLA-absorb path run
  5. · Evidence links · GitHub search · DeepSeek · pulls · NVIDIA/TensorRT-LLM · @moraxu
  6. · Evidence links · GitHub search · DeepSeek · pulls · NVIDIA/TensorRT-LLM · @farazkh80
    Excerpt
    with all of its KV remote and MLA (DeepSeek-R1 shape) 1.43x, which is why allocation and placement keep pages local. Partitioned attention rejects FlashMLA, beam
  7. · Catalogue listing · GitHub · openai/openai-agents-python · code
    Excerpt
    object="chat.completion.chunk", choices=[Choice(index=0, delta=delta)], ) for delta in [*reasoning_deltas, ChoiceDelta(content="answer")] ] events = await _collect_handler_events(*chunks, model="deepseek-r1") completed_event = next(event for event in events if event.type == "response.completed") reasoning_item = completed_event.response.output[0] assert isinstance(reasoning_item, ResponseReasoningItem) assert reasoning_item.summary[0].text == "summary" assert reasoning_item.content assert [part.text for part in reasoning_item.content] == ["raw"] assert "_chat_completions_reasoning_field" not in cast(Any, reasoning_item).provider_data replayed_messages = Converter.items_to_messages( [item.model_dump() for item in completed_event.response.output], model="deepseek-r1", ) assert len

    This code reference does not establish a working model identifier.

Signals 1

Specifications

DeepSeek R1 is a model from DeepSeek with open weights, released on 20 Jan 2025. The context window is 64,000 tokens.

Context window
64,000
Weights
Open

Questions

What is the context window of DeepSeek R1?

The context window is 64,000 tokens.

Are the weights of DeepSeek R1 publicly available?

Yes. DeepSeek publishes the weights.

When was DeepSeek R1 released?

On 20 Jan 2025.