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URL: https://willitrunai.com/models/hf-richarderkhov--stabilityai---japanese-stablelm-instruct-beta-70b-gguf

⇱ stabilityai japanese stablelm instruct beta 70b VRAM Requirements — GPU Compatibility


RichardErkhov

stabilityai japanese stablelm instruct beta 70b

Limited data available — some specs may be incomplete or estimated.
0K tokensContextUnknownLicense3 EntryQuality

stabilityai japanese stablelm instruct beta 70b (70B parameters) requires approximately 52.7 GB of VRAM with Q4_K_M quantization. For the best balance of quality and speed, we recommend hardware with at least 61 GB of VRAM.

Quick specs

Parameters70B
Architecturedense
Context0K tokens
Modalitytext
Min RAM27.3 GB
Rec. RAM42.7 GB (Q4_K_M)
LicenseUnknown
FamilyUnknown
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Your hardware

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Quick picks

Best budgetC
MacBook Pro M3 Max 128GB~$2,499 — 6 tok/s
👁 NVIDIA
Best overallB
NVIDIA H100 80GB~$40,000 — 66 tok/s

Best hardware

Top picks for stabilityai japanese stablelm instruct beta 70b

NVIDIA H100 80GBB
80 GB
NVIDIA H800 80GBC
80 GB
NVIDIA GH200 96GBC
96 GB
NVIDIA H20 96GBC
96 GB
NVIDIA A100 80GBC
80 GB

Run this model

stabilityai japanese stablelm instruct beta 70b on NVIDIA H100 80GBstabilityai japanese stablelm instruct beta 70b on NVIDIA H800 80GBstabilityai japanese stablelm instruct beta 70b on NVIDIA GH200 96GB

Quantization options

VRAM estimates by quant level

No hardware detected — fit column shows raw VRAM estimates

QuantBitsVRAMQualityFit
Q2_K
2
27.3 GB
Low
Q3_K_S
3
34.3 GB
Low
NVFP4
4
39.2 GB
Medium
Q4_K_M
4
42.7 GB
Medium
Q5_K_M
5
50.4 GB
High
Q6_K
6
57.4 GB
High
Q8_0
8
74.9 GB
Very High
F16
16
143.5 GB
Maximum

Hardware compatibility

Fit estimates across all hardware

Open calculator

Computing compatibility...

Memory breakdown

Reference: RTX 2060 6GB

Weights42.7 GB
KV Cache8.2 GB
Runtime1.2 GB
Headroom0.6 GB

Frequently asked questions

FAQ — stabilityai japanese stablelm instruct beta 70b

See also

Quantization GuideScoring MethodologyVRAM Calculator