deepseek-ai

DeepSeek-R1-Distill-Llama-8B

8B parameters · reasoning · Reasoning · DeepSeek family

Long context — how it uses memory →
mit hash verified source matched revision pinned

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Default pick: GGUF · Q4_K_M — Balanced size/quality — good default.

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Quantizations

Why these quants? Which quant should I pick? What do these mean?

GGUF · IQ4_XS

4.16 GB

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Est. speed
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Swarm
2S / 0L webseed OK

Unsloth IQ4_XS quant of DeepSeek-R1-Distill-Llama-8B (8.03B dense) — compact low-bit option. MIT.

Magnet .torrent

GGUF · Q4_K_M

4.58 GB

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Swarm
2S / 0L webseed OK

Balanced size/quality — good default.

Magnet .torrent

GGUF · Q8_0

7.95 GB

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Est. speed
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Swarm
2S / 0L webseed OK

Unsloth Q8_0 quant of DeepSeek-R1-Distill-Llama-8B (8.03B dense) — high-quality option. MIT.

Magnet .torrent

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Runs fully on

RTX 5090 · Q8_0 RTX 5060 Ti 16GB · Q8_0 RTX 5070 Ti · Q8_0 RTX 5080 · Q8_0 RTX 5070 · Q8_0

Green = the model's best quant fits fully in GPU/unified memory at 8K context. Tap a card for its full "what runs on it" page.

Context

Advertised 128k · no independent evidence yet

No independent long-context evidence has been graded for this model yet — the advertised window above is the maintainer's number, not a usable-context claim.

Capabilities (as declared by the maintainer): reasoning tool calling

Run it

Runtime completeness (IQ4_XS torrent): llama.cpp ✅ Ollama – vision sidecar –

  • – Ollama — runs the GGUF directly; no Modelfile bundled
  • – vision sidecar — not a vision model

Context / KV 8,192 tokens · FP16 set above the quant table

Generic commands (no rig set). GPU-offload values assume the model fits on your GPU — set your rig for values tuned to your hardware.

Start the server 
llama-server -m DeepSeek-R1-Distill-Llama-8B-IQ4_XS.gguf -c 8192 -ngl 999

Use llama-cli in place of llama-server for a one-shot prompt.

Save as Modelfile next to the GGUF (Modelfile) 
FROM ./DeepSeek-R1-Distill-Llama-8B-IQ4_XS.gguf
PARAMETER num_ctx 8192
PARAMETER num_gpu 999
PARAMETER stop "<｜end▁of▁sentence｜>"
PARAMETER temperature 0.6
PARAMETER top_p 0.95
# Chat template: Ollama uses the template embedded in the GGUF (no TEMPLATE directive needed).
Create 
ollama create deepseek-ai-deepseek-r1-distill-llama-8b -f Modelfile
Run 
ollama run deepseek-ai-deepseek-r1-distill-llama-8b

GGUF is not a first-class vLLM format.

vLLM GGUF support is experimental and single-file only; prefer safetensors/GPTQ/AWQ for production. If you must, pass the .gguf path to `vllm serve` with --load-format gguf on a recent vLLM.

transformers does not load GGUF weights.

GGUF weights run under llama.cpp, Ollama or LM Studio.

Load DeepSeek-R1-Distill-Llama-8B-IQ4_XS.gguf, set the context length to 8192 tokens. Set GPU offload to Max (all layers).

MLX runs MLX-format weights only (Apple Silicon). This quant is a GGUF build.

GGUF weights run under llama.cpp, Ollama or LM Studio.

Technical details

Chat template

{% if not add_generation_prompt is defined %}{% set add_generation_prompt = false %}{% endif %}{% set ns = namespace(is_first=false, is_tool=false, is_output_first=true, system_prompt='') %}{%- for message in messages %}{%- if message['role'] == 'system' %}{% set ns.system_prompt = message['content'] %}{%- endif %}{%- endfor %}{{bos_token}}{{ns.system_prompt}}{%- for message in messages %}{%- if message['role'] == 'user' %}{%- set ns.is_tool = false -%}{{'<｜User｜>' + message['content']}}{%- endif %}{%- if message['role'] == 'assistant' and message['content'] is none %}{%- set ns.is_tool = false -%}{%- for tool in message['tool_calls']%}{%- if not ns.is_first %}{{'<｜Assistant｜><｜tool▁calls▁begin｜><｜tool▁call▁begin｜>' + tool['type'] + '<｜tool▁sep｜>' + tool['function']['name'] + '\n' + '```json' + '\n' + tool['function']['arguments'] + '\n' + '```' + '<｜tool▁call▁end｜>'}}{%- set ns.is_first = true -%}{%- else %}{{'\n' + '<｜tool▁call▁begin｜>' + tool['type'] + '<｜tool▁sep｜>' + tool['function']['name'] + '\n' + '```json' + '\n' + tool['function']['arguments'] + '\n' + '```' + '<｜tool▁call▁end｜>'}}{{'<｜tool▁calls▁end｜><｜end▁of▁sentence｜>'}}{%- endif %}{%- endfor %}{%- endif %}{%- if message['role'] == 'assistant' and message['content'] is not none %}{%- if ns.is_tool %}{{'<｜tool▁outputs▁end｜>' + message['content'] + '<｜end▁of▁sentence｜>'}}{%- set ns.is_tool = false -%}{%- else %}{% set content = message['content'] %}{% if '</think>' in content %}{% set content = content.split('</think>')[-1] %}{% endif %}{{'<｜Assistant｜>' + content + '<｜end▁of▁sentence｜>'}}{%- endif %}{%- endif %}{%- if message['role'] == 'tool' %}{%- set ns.is_tool = true -%}{%- if ns.is_output_first %}{{'<｜tool▁outputs▁begin｜><｜tool▁output▁begin｜>' + message['content'] + '<｜tool▁output▁end｜>'}}{%- set ns.is_output_first = false %}{%- else %}{{'\n<｜tool▁output▁begin｜>' + message['content'] + '<｜tool▁output▁end｜>'}}{%- endif %}{%- endif %}{%- endfor -%}{% if ns.is_tool %}{{'<｜tool▁outputs▁end｜>'}}{% endif %}{% if add_generation_prompt and not ns.is_tool %}{{'<｜Assistant｜><think>\n'}}{% endif %}

Sampling defaults

top_p
0.95
temperature
0.6

Stop strings

<｜end▁of▁sentence｜>

Evidence & provenance

Source

Provenance
https://huggingface.co/deepseek-ai/DeepSeek-R1-Distill-Llama-8B
Revision pin
6a6f4aa4197940add57724a7707d069478df56b1
Manifest
Present

License

Name
mit
Commercial use
yes
Access
Open

How verification works →

File hashes (SHA-256)

  • deepseek-r1-distill-llama-8b-iq4-xs/DeepSeek-R1-Distill-Llama-8B-IQ4_XS.gguf df6473076371976320dc13339fed94e1532c84ef3b3f4b2eeaf0fe0f19ed7376
  • deepseek-r1-distill-llama-8b-iq4-xs/LICENSE 1c8f573e830ca9b3ebfeb7ace1823146e22b66f99ee223840e7637c9e745e1c7
  • deepseek-r1-distill-llama-8b-iq4-xs/README.md 7cceac136dec35b7fc92453c7ddd03b3bfb2a5b804203a87c929a5b0d17d2c95
  • deepseek-r1-distill-llama-8b-q4-k-m/DeepSeek-R1-Distill-Llama-8B-Q4_K_M.gguf 87bcba20b4846d8dadf753d3ff48f9285d131fc95e3e0e7e934d4f20bc896f5d
  • deepseek-r1-distill-llama-8b-q4-k-m/LICENSE 1c8f573e830ca9b3ebfeb7ace1823146e22b66f99ee223840e7637c9e745e1c7
  • deepseek-r1-distill-llama-8b-q4-k-m/README.md 7cceac136dec35b7fc92453c7ddd03b3bfb2a5b804203a87c929a5b0d17d2c95
  • deepseek-r1-distill-llama-8b-q8-0/DeepSeek-R1-Distill-Llama-8B-Q8_0.gguf 8c6e3924d662d3f24a96b228a5c317510c27e91c587e71e78877ed18a875ec82
  • deepseek-r1-distill-llama-8b-q8-0/LICENSE 1c8f573e830ca9b3ebfeb7ace1823146e22b66f99ee223840e7637c9e745e1c7
  • deepseek-r1-distill-llama-8b-q8-0/README.md 7cceac136dec35b7fc92453c7ddd03b3bfb2a5b804203a87c929a5b0d17d2c95

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Appears in

What runs on 8 GB of VRAM What runs on 12 GB of VRAM What runs on 16 GB of VRAM What runs on a 16 GB Mac What runs on a 24 GB Mac Coding models that fit 8 GB

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