InternLM3 8B Instruct: local hardware requirements and GPU compatibility
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Local AI model

InternLM3 8B Instruct

by Shanghai AI Laboratory

12 of 22 reference machines run it entirely in accelerator memory at 8k context, and 1 more with CPU offload.

8.8B Parameters 32k Maximum context 2 Quantization Full Compatibility coverage
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Overview

Publisher
Shanghai AI Laboratory
Family
Internlm
Series
InternLM3
Task
Text generation
Architecture
dense · internlm3
Parameters
8.8B
Maximum context
32,768 tokens
Licence
apache-2.0
Published
2025-01-13
Formats
gguf, safetensors
KV cache per token (f16)
49,152 B · standard attention, exact
Compatibility coverage
Full: verdicts computed
Upstream repository
internlm/internlm3-8b-instruct
Official page
https://internlm.intern-ai.org.cn/

Quantizations and file sizes

Quantization Runtime Weights Memory floor at 4k Identity
Q4_K_Mgguf llama.cppinternlm/internlm3-8b-instruct-gguf/internlm3-8b-instruct-q4_k_m.gguf 4.99 GB 5.18 GB digest verified
Q8_0gguf llama.cppinternlm/internlm3-8b-instruct-gguf/internlm3-8b-instruct-q8_0.gguf 8.72 GB 8.90 GB digest verified

Sizes come from the runtime registry or repository listing. The memory floor adds the KV cache for 4,096 tokens when that figure cannot over-count; it is an estimate, not a requirement.

Runtimes

Compatibility on reference machines

8k context, 32 GB system RAM, best catalogued quantization per machine.

Machine Memory Answer Known facts
GeForce RTX 4060 8GB 8.00 GB VRAM Runs fully in memory estimated · Q4_K_M Weights 4.99 GB vs 8.00 GB VRAM: fitKV cache at 8k: 0.38 GB
GeForce RTX 3080 10GB 10.0 GB VRAM Runs fully in memory estimated · Q4_K_M Weights 4.99 GB vs 10.0 GB VRAM: fitKV cache at 8k: 0.38 GB
GeForce RTX 3060 12GB 12.0 GB VRAM Runs fully in memory estimated · Q8_0 Weights 8.72 GB vs 12.0 GB VRAM: fitKV cache at 8k: 0.38 GB
GeForce RTX 4070 12GB 12.0 GB VRAM Runs fully in memory estimated · Q8_0 Weights 8.72 GB vs 12.0 GB VRAM: fitKV cache at 8k: 0.38 GB
GeForce RTX 5070 12GB 12.0 GB VRAM Runs fully in memory estimated · Q8_0 Weights 8.72 GB vs 12.0 GB VRAM: fitKV cache at 8k: 0.38 GB
GeForce RTX 4060 Ti 16GB 16.0 GB VRAM Runs fully in memory estimated · Q8_0 Weights 8.72 GB vs 16.0 GB VRAM: fitKV cache at 8k: 0.38 GB
GeForce RTX 4080 16GB 16.0 GB VRAM Runs fully in memory estimated · Q8_0 Weights 8.72 GB vs 16.0 GB VRAM: fitKV cache at 8k: 0.38 GB
GeForce RTX 5060 Ti 16GB 16.0 GB VRAM Runs fully in memory estimated · Q8_0 Weights 8.72 GB vs 16.0 GB VRAM: fitKV cache at 8k: 0.38 GB
GeForce RTX 5080 16GB 16.0 GB VRAM Runs fully in memory estimated · Q8_0 Weights 8.72 GB vs 16.0 GB VRAM: fitKV cache at 8k: 0.38 GB
GeForce RTX 3090 24GB 24.0 GB VRAM Runs fully in memory estimated · Q8_0 Weights 8.72 GB vs 24.0 GB VRAM: fitKV cache at 8k: 0.38 GB
GeForce RTX 4090 24GB 24.0 GB VRAM Runs fully in memory estimated · Q8_0 Weights 8.72 GB vs 24.0 GB VRAM: fitKV cache at 8k: 0.38 GB
GeForce RTX 5090 32GB 32.0 GB VRAM Runs fully in memory estimated · Q8_0 Weights 8.72 GB vs 32.0 GB VRAM: fitKV cache at 8k: 0.38 GB
GeForce RTX 3060 Laptop GPU 6GB 6.00 GB VRAM Runs with CPU offload estimated · Q8_0 Weights 8.72 GB vs 6.00 GB VRAM: do not fitKV cache at 8k: 0.38 GB
Radeon RX 7600 8GB 8.00 GB VRAM Not enough data not verified · Q4_K_M Weights 4.99 GB vs 8.00 GB VRAM: fitKV cache at 8k: 0.38 GBruntime support on this machine: unknown
Intel Arc B580 12GB 12.0 GB VRAM Not enough data not verified · Q4_K_M Weights 4.99 GB vs 12.0 GB VRAM: fitKV cache at 8k: 0.38 GBruntime support on this machine: unknown
Radeon RX 7800 XT 16GB 16.0 GB VRAM Not enough data not verified · Q4_K_M Weights 4.99 GB vs 16.0 GB VRAM: fitKV cache at 8k: 0.38 GBruntime support on this machine: unknown
Radeon RX 9070 XT 16GB 16.0 GB VRAM Not enough data not verified · Q4_K_M Weights 4.99 GB vs 16.0 GB VRAM: fitKV cache at 8k: 0.38 GBruntime support on this machine: unknown
Intel Arc A770 16GB 16.0 GB VRAM Not enough data not verified · Q4_K_M Weights 4.99 GB vs 16.0 GB VRAM: fitKV cache at 8k: 0.38 GBruntime support on this machine: unknown
Radeon RX 7900 XTX 24GB 24.0 GB VRAM Not enough data not verified · Q4_K_M Weights 4.99 GB vs 24.0 GB VRAM: fitKV cache at 8k: 0.38 GBruntime support on this machine: unknown
Mac mini M4 24GB 24.0 GB unified Not enough data not verified · Q4_K_M Weights 4.99 GB vs 24.0 GB unified: fitKV cache at 8k: 0.38 GBruntime support on this machine: unknown
Mac mini M4 Pro 24GB 24.0 GB unified Not enough data not verified · Q4_K_M Weights 4.99 GB vs 24.0 GB unified: fitKV cache at 8k: 0.38 GBruntime support on this machine: unknown
MacBook Pro 14-inch M4 Max 36GB 36.0 GB unified Not enough data not verified · Q4_K_M Weights 4.99 GB vs 36.0 GB unified: fitKV cache at 8k: 0.38 GBruntime support on this machine: unknown

Definitive answers ("runs", "does not fit") come from the calibrated engine or a physical run. "Potential" rows only compare the weights with memory: the rest of the requirement is not modelled, so they are not verdicts. Unknown is never a failure.

Hardware for this model

Reference GPUs with 8 GB of VRAM or more run this model entirely in memory at 8k context: GeForce RTX 4060 8GB, GeForce RTX 3080 10GB, GeForce RTX 3060 12GB, GeForce RTX 4070 12GB.

  • Smallest catalogued artifact: 4.99 GB of weights (Q4_K_M).
  • A GPU with at least 8 GB of VRAM holds those weights.
Explore 8 GB VRAM GPUs
These links open a hardware category search, not a specific product recommendation. Affiliate link — I may earn a commission from qualifying purchases. These links never change a compatibility answer. They follow the memory the data defends, not commission.

Sources and evidence

0 measured, 37 sourced, 4 estimated and 5 unknown fields.

Catalogue record verified 2026-09-17.

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