stabilityai
japanese-stablelm-instruct-beta-70b
- Parameters
- 69B
- Max context length
- 4,096
- Architecture
- llama
- License
- Conditional
- License
- llama2
About japanese-stablelm-instruct-beta-70b
japanese-stablelm-instruct-beta-70b is a GGUF model based on stabilityai/japanese-stablelm-instruct-beta-70b on Hugging Face. GGUF files are published by TheBloke/japanese-stablelm-instruct-beta-70B-GGUF. It has about 69B parameters, the llama architecture, a maximum context length of 4,096 tokens (values written in the GGUF).
There are 10 quantizations, with file sizes from 29.3 GB (Q2_K) to 48.8 GB (Q5_K_M) (actual sizes on Hugging Face).
The original model is licensed under Llama 2 Community License, which allows commercial use with conditions such as scale or purpose. Check the original license for the terms of use.
File size and estimated memory per quantization
- Up to 8 GB
- Up to 16 GB
- Up to 24 GB
- Up to 48 GB
- Up to 128 GB
- More
File sizes are the actual values on Hugging Face. Memory is estimated for each context length (KV cache f16). The formula is in How memory is calculated.
All memory figures are Estimated (KV cache f16). It should run on a setup with at least this much VRAM (or Mac unified memory). Click a value to see the devices and models that fit that amount (Find by GPU / Mac).
About the "quality guide" (how far a quantization drifts from the original)
For each quantization type, how far the output drifts from the original model, grouped into six levels from values llama.cpp measured on Llama-3-8B.
The value is mean KLD (the difference between the original and quantized model in next-token probabilities); smaller means closer to the original. Quantizations made with an imatrix (importance data) come out slightly smaller. Levels use the value without an imatrix (or with one, for types that only have that).
These values were not measured on this model. Larger models and MoE models tend to drift less with the same type. Distributor-specific mixed types (such as UD-Q4_K_XL) cannot be matched by type name alone, so they show "-".
| Quantization | Quality guide | KLD (no imatrix) | KLD (imatrix) | Size (Llama-3-8B) |
|---|---|---|---|---|
| Q8_0 | Nearly identical | 0.0014 | - | 7.96 GiB |
| Q6_K | Very small | 0.0055 | - | 6.14 GiB |
| Q5_K_M | Very small | 0.0108 | - | 5.33 GiB |
| Q5_K_S | Small | 0.0166 | - | 5.21 GiB |
| Q5_1 | Small | 0.0180 | - | 5.65 GiB |
| Q5_0 | Small | 0.0222 | - | 5.21 GiB |
| Q4_K_M | Small | 0.0313 | 0.0282 | 4.58 GiB |
| Q4_K_S | Medium | 0.0431 | 0.0320 | 4.37 GiB |
| IQ4_NL | Small | - | 0.0357 | 4.35 GiB |
| IQ4_XS | Small | - | 0.0363 | 4.14 GiB |
| Q4_1 | Medium | 0.0717 | - | 4.78 GiB |
| Q4_0 | Medium | 0.0719 | - | 4.34 GiB |
| Q3_K_L | Medium | 0.0872 | 0.0731 | 4.03 GiB |
| Q3_K_M | Medium | 0.1019 | 0.0844 | 3.74 GiB |
| IQ3_M | Medium | - | 0.1025 | 3.53 GiB |
| IQ3_S | Medium | - | 0.1113 | 3.42 GiB |
| IQ3_XS | Large | - | 0.1387 | 3.28 GiB |
| IQ3_XXS | Large | - | 0.1836 | 3.05 GiB |
| Q3_K_S | Large | 0.2282 | 0.1998 | 3.41 GiB |
| IQ2_M | Large | - | 0.3260 | 2.74 GiB |
| Q2_K | Very large | 0.4451 | 0.3322 | 2.96 GiB |
| Q2_K_S | Very large | - | 0.4034 | 2.96 GiB |
| IQ2_S | Very large | - | 0.4392 | 2.56 GiB |
| IQ2_XS | Very large | - | 0.5463 | 2.43 GiB |
| IQ2_XXS | Very large | - | 0.8120 | 2.24 GiB |
| IQ1_M | Very large | - | 1.3931 | 2.01 GiB |
| IQ1_S | Very large | - | 2.2546 | 1.88 GiB |
Source: llama.cpp (MIT), measured on Llama-3-8B against FP16, Wikitext-2, revision f364eb6f. Original table · Reading and choosing quantizations
GGUF source
TheBloke/japanese-stablelm-instruct-beta-70B-GGUF
Converted and published by a third party About this label
Last checked: Nov 11, 2026
- Architecture
- llama
- Supported before llama.cpp b4409
- Parameters
- 69.0B
- Max context length
- 4,096
- License
- llama2 Conditional
| Quantization | File size Measured | Quality guide | 4,096 max |
|---|---|---|---|
| Q2_K | 29.3 GB | Very large | 31.2 GB |
| Q3_K_S | 29.9 GB | Large | 31.9 GB |
| Q3_K_M | 33.2 GB | Medium | 35.1 GB |
| Q3_K_L | 36.1 GB | Medium | 38.1 GB |
| Q4_0 | 38.9 GB | Medium | 40.8 GB |
| Q4_K_S | 39.1 GB | Medium | 41.0 GB |
| Q4_K_M | 41.4 GB | Small | 43.4 GB |
| Q5_0 | 47.5 GB | Small | 49.4 GB |
| Q5_K_S | 47.5 GB | Small | 49.4 GB |
| Q5_K_M | 48.8 GB | Very small | 50.7 GB |
Ollama ollama run hf.co/TheBloke/japanese-stablelm-instruct-beta-70B-GGUF:Q4_K_M
llama.cpp llama-server -hf TheBloke/japanese-stablelm-instruct-beta-70B-GGUF:Q4_K_M
License and commercial use
Llama 2 Community License Conditional
Allows commercial use. However, products or services with more than 700 million monthly active users need a separate license from Meta. You must follow the Acceptable Use Policy.
Based on the license on the original model's Hugging Face page. Original license text (checked Oct 18, 2026)
The summary states facts this site read from the original text and is not legal advice. Always check the original license and its latest terms before use. All licenses
How to run
Example commands using Q4_K_M. To use another quantization, replace the name with one from the table above. How to run local LLMs
Ollama
Run it by pointing directly at the GGUF on Hugging Face.
ollama run hf.co/TheBloke/japanese-stablelm-instruct-beta-70B-GGUF:Q4_K_M
llama.cpp
Pass the repository and quantization name to llama-server (or llama-cli) with -hf.
llama-server -hf TheBloke/japanese-stablelm-instruct-beta-70B-GGUF:Q4_K_M
LM Studio
Paste TheBloke/japanese-stablelm-instruct-beta-70B-GGUF into the search box, download it, and choose the quantization from the file list.
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Frequently asked questions
- How much memory do I need to run japanese-stablelm-instruct-beta-70b (Q4_K_M)?
- The file size is 41.4 GB (measured). With a 4,096-token context, the estimated memory including the KV cache is 43.4 GB. The formula is published at https://localllm.az-arte.com/en/guide/memory-calculation.
- Can japanese-stablelm-instruct-beta-70b be used commercially?
- The original model's license is Llama 2 Community License (Commercial use with conditions).Allows commercial use. However, products or services with more than 700 million monthly active users need a separate license from Meta. You must follow the Acceptable Use Policy. Check the original license text before deciding.
- What is the command to run japanese-stablelm-instruct-beta-70b with Ollama?
- Run "ollama run hf.co/TheBloke/japanese-stablelm-instruct-beta-70B-GGUF:Q4_K_M" to use the GGUF on Hugging Face directly. To use another quantization, replace the name at the end.