Snowflake Arctic Instruct — Hardware Requirements & GPU Compatibility
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Snowflake Arctic Instruct is a 478.6B-parameter open language model from Snowflake. It supports a context window of up to 4,096 tokens. At BF16 it needs about 957.76 GB of VRAM — see which GPUs and Macs can run it below.
Snowflake Arctic Instruct runs on a multi-GPU server
BF16 needs ~958.1 GB · about 8× H200 SXM 141 GB
Apache 2.0
Not set up for it?
Reference GPU · RTX 4090 24 GB
Estimates, ±20% · how we estimate
Run Snowflake Arctic Instruct
One recommended way. Every other method, OS and quant is in the step-by-step guide.
Recommended
vllm serve Snowflake/snowflake-arctic-instruct --max-model-len 4096 --tensor-parallel-size 8Size the nodes from the table above
Download: Weights on Hugging Face
Other ways
each opens step-by-stepRun in cloud
Rent 8× H200 SXM node · BF16
- Estimated hourly price
- ~$28.72/hr
- est., whole server
- GPUs
- 8 GPUs
- 1.1 TB of VRAM
How Much VRAM Does Snowflake Arctic Instruct Need?
Select a quantization level; the listed hardware adheres to it.
| Quantization | VRAM | +32K | Runs on | |
|---|---|---|---|---|
| 957.8 GB | — | 16-bit · bfloat — Brain floating point 16 — preferred for training | Runs on 8× H200 SXM 141 GB |
Selected BF16
Brain floating point 16958.1GBat 4K context
- Weights
- 957.2 GB
- KV cache
- 0.6 GB
- Overhead
- 0.3 GB
Server-class: ~958.1 GB at 4K context · about 8× H200 SXM 141 GB
Which Hardware Can Run Snowflake Arctic Instruct?
BF16 · 957.8 GBSnowflake Arctic Instruct (BF16) requires 957.8 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 1246+ GB is recommended. Using the full 4K context window can add up to 0.3 GB, bringing total usage to 958.1 GB. No consumer GPU has enough memory.
Needs server-class hardware
Snowflake Arctic Instruct runs on a multi-GPU server · BF16 needs ~958.1 GB
| Hardware | Quant | Memory | Context | Hardware page | |
|---|---|---|---|---|---|
| 8× H200 SXM 141 GB · 1.1 TB | BF16 | 958.1 GB | 4K ctx | H200 SXM → | BF16 · 958.1 GB · 4K ctx |
| 6× B200 192 GB · 1.2 TB | BF16 | 958.1 GB | 4K ctx | B200 → | BF16 · 958.1 GB · 4K ctx |
By VRAM tier · typical GPUs and Macs at BF16
Consumer GPUs (up to 32 GB) and Macs up to 512 GB: too small for this model (needs ≥ 958.1 GB)8 GB tier →12 GB tier →16 GB tier →24 GB tier →Macs →
How good is Snowflake Arctic Instruct?
llmrun Score blends public benchmark boards into one number; 100 = the average open model.
Not enough data yet for an llmrun Score.
A Score needs results on enough independent boards. How the Composite Score is built
Benchmarks
This is the single board showing results for this model; badges show who ran the test.
- LMArena Text
LMArena · Oct 2026Arena
Arena1180.2
#155/187 open
Similar models
1| Model | Score | VRAM | tok/s | Why it is similar |
|---|---|---|---|---|
| MiniMax VL 01MiniMax | — | 915.2 GB | —needs > 24 GB | same size |
Specifications
- Publisher
- Snowflake
- Parameters
- 478.6B
- Active parameters
- 17.3B per token
- Architecture
- ArcticForCausalLM
- Context Length
- 4,096 tokens
- Vocabulary Size
- 32,000
- Release Date
- 2024-04-21
- License
- Apache 2.0
Frequently Asked Questions
How much VRAM does Snowflake Arctic Instruct need?
Snowflake Arctic Instruct requires 957.8 GB of VRAM at BF16.
VRAM = Weights + KV Cache + Overhead
Weights = 478.6B × 16 bits ÷ 8 = 957.2 GB
KV Cache + Overhead ≈ 0.6 GB (at 2K context + ~0.3 GB framework)
Fit ratings and hardware model lists check this model with room for a 16K-token context, which needs a little more memory.
KV Cache + Overhead ≈ 0.9 GB (at full 4K context)
VRAM usage by quantization
Can NVIDIA GeForce RTX 5090 run Snowflake Arctic Instruct?
No — Snowflake Arctic Instruct requires at least 957.8 GB at BF16, which exceeds the NVIDIA GeForce RTX 5090's 32 GB of VRAM.
Can I run Snowflake Arctic Instruct on a Mac?
Snowflake Arctic Instruct requires at least 957.8 GB at BF16. None of the 146 Macs we list has that much usable memory (the largest has 508.5 GB after macOS overhead).
Can I run Snowflake Arctic Instruct locally?
Yes — Snowflake Arctic Instruct can run locally on consumer hardware. Popular tools include Ollama, LM Studio, and llama.cpp.
What's the download size of Snowflake Arctic Instruct?
At BF16, the download is about 957.17 GB.
Which GPUs can run Snowflake Arctic Instruct?
No single consumer GPU has enough VRAM to run Snowflake Arctic Instruct at BF16 (957.8 GB). Multi-GPU or professional hardware is required.
Which devices can run Snowflake Arctic Instruct?
Snowflake Arctic Instruct requires at least 957.8 GB at BF16, which exceeds the usable memory of every unified-memory device we list (the largest has 508.5 GB).