deepseek-ai

DeepSeek-R1-Distill-Qwen-1.5B

1.8B parameters · reasoning · Reasoning · DeepSeek family

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

Which version should I download?

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

Set your rig to confirm it fits and to see if a higher-quality quant runs fully on your hardware.

Set your rig

Quantizations

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

GGUF · Q4_K_M

1.04 GB

Set your rig
Est. speed
—
Swarm
2S / 0L webseed OK

Balanced size/quality — good default.

Magnet .torrent

GGUF · Q8_0

1.76 GB

Set your rig
Est. speed
—
Swarm
2S / 0L webseed OK

Unsloth Q8_0 quant of DeepSeek-R1-Distill-Qwen-1.5B (1.777B dense) — high-quality option. MIT.

Magnet .torrent

Want a different quant? Request it on the board →

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 (Q4_K_M torrent): llama.cpp ✅ Ollama – vision sidecar –

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

Runtime verified: generation-verified · llama.cpp b9957

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-Qwen-1.5B-Q4_K_M.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-Qwen-1.5B-Q4_K_M.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-qwen-1-5b -f Modelfile
Run 
ollama run deepseek-ai-deepseek-r1-distill-qwen-1-5b

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-Qwen-1.5B-Q4_K_M.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-Qwen-1.5B
Revision pin
ad9f0ae0864d7fbcd1cd905e3c6c5b069cc8b562
Manifest
Present

License

Name
mit
Commercial use
yes
Access
Open

How verification works →

File hashes (SHA-256)

  • deepseek-r1-distill-qwen-1.5b-q4-k-m/DeepSeek-R1-Distill-Qwen-1.5B-Q4_K_M.gguf 1741e5b2d062b07acf048bf0d2c514dadf2a48f94e2b4aa0cfe069af3838ee2f
  • deepseek-r1-distill-qwen-1.5b-q4-k-m/LICENSE 1c8f573e830ca9b3ebfeb7ace1823146e22b66f99ee223840e7637c9e745e1c7
  • deepseek-r1-distill-qwen-1.5b-q4-k-m/README.md b46c5328333e9442c34484e1bfd51b0643e353743a6bf4fa296cb6c61ad2e35f
  • deepseek-r1-distill-qwen-1.5b-q8-0/DeepSeek-R1-Distill-Qwen-1.5B-Q8_0.gguf 068a721e47419ccfc94b6420118f772478544e1a0d4fad7118212774b3f9ba9e
  • deepseek-r1-distill-qwen-1.5b-q8-0/LICENSE 1c8f573e830ca9b3ebfeb7ace1823146e22b66f99ee223840e7637c9e745e1c7
  • deepseek-r1-distill-qwen-1.5b-q8-0/README.md b0f94d4b228b3c370c19f4ef2d1c56181082d761cb663f3748605a9d9a2f87c6

Explore further

Appears in

What runs on 6 GB of VRAM What runs on 8 GB of VRAM What runs on a 8 GB Mac Coding models that fit 6 GB Coding models that fit 8 GB Writing models that fit 6 GB

Also consider

Get an email when a better quant fits your rig.

Set your rig once; we'll alert you when a new or better-fitting build lands.

Set your rig

Performance reports

Real-world throughput reported by the community (and scraped sources).

View performance leaderboard
Community

Reviews, sampler presets and community runtime reports. Be the first to contribute.

Reviews (0)

Log in to write a structured review of this model.

No reviews yet.

Sampler presets

Log in to share a sampler preset or vote on presets.

No presets yet.

Community runtime reports

Unofficial, community-submitted "it loads for me" reports. These are not the official verified-working badge — an admin reviews reports before anything is marked officially verified.

Log in to report whether a quant loads in your runtime.

No community reports yet.

selected to compare · pick at least 2

Compare ()