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text model · Sarvam · Windows

Can I run Sarvam-105B on Nvidia GeForce RTX 5090 (32GB)?

Compatibility verdict VRAM threshold engine
No, not enough memory would not load

No. Sarvam-105B needs ~67.5 GB even at Q4_K_M, but Nvidia GeForce RTX 5090 (32GB) only has ~31 GB usable.

Needs ~67.5 GB Device usable ~31 GB

Needs ~67.5 GB even at Q4_K_M, but only ~31 GB is usable.

That figure is at a 4k context and moves about ±15% as context length changes.

The gap is about 36.5 GB: Sarvam-105B needs roughly 67.5 GB at Q4_K_M and Nvidia GeForce RTX 5090 (32GB) leaves only about 31 GB usable for a model. The lightest tracked hardware that runs Sarvam-105B is the Apple M4 Max (128GB) at 128 GB. See Sarvam-105B on Apple M4 Max (128GB).

Q4_K_M needed
~67.5 GB
Usable on device
~31 GB
Device memory
32 GB
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Which quant fits

Quant ladder vs ~31 GB usable
Q2_K
~47.3 GB
Q3_K_M
~54.6 GB
Q4_K_M
~67.5 GB
Q5_K_M
~78.1 GB
Q6_K
~89.4 GB
Q8_0
~114.9 GB
FP16
~213.3 GB
The line marks Nvidia GeForce RTX 5090 (32GB)'s ~31 GB budget; rungs past it are too large.

How to run it

On Windows use LM Studio (Best GUI on Windows, auto-detects CUDA/Vulkan backends.).

Model Sarvam
Parameters
105B (MoE, 10.3B active)
Q4_K_M size
64.2 GB
Context
128k
Full Sarvam-105B requirements →
Device Windows
Memory
32 GB vram
Usable for weights
~31 GB
Power draw
~575 W
Best runtime
vLLM (Linux) / Ollama (CUDA)
Best models for Nvidia GeForce RTX 5090 (32GB) →

What you can run instead

Run Sarvam-105B on other hardware

FAQ

Can Nvidia GeForce RTX 5090 (32GB) run Sarvam-105B?

No. Sarvam-105B needs ~67.5 GB even at Q4_K_M, but Nvidia GeForce RTX 5090 (32GB) only has ~31 GB usable.

How much memory does Sarvam-105B need?

Nvidia GeForce RTX 5090 (32GB) does not have enough memory. At Q4_K_M the weights are ~64.2 GB; with KV cache and runtime overhead, budget ~67.5 GB at a 4k context. It is a Mixture-of-Experts model (105B total / 10.3B active), so all experts must stay in memory; memory tracks total params, not active params.

What is the best tool to run Sarvam-105B on Windows?

LM Studio for a simple setup; Ollama (CUDA) for the most speed. AMD GPUs run via Vulkan/ROCm at roughly half CUDA throughput. NVIDIA is the smooth path on Windows.

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Sources

Weights are measured from GGUF files; KV cache and overhead are computed, so totals can vary ~15% with context and runtime. Any tok/s is a bandwidth estimate. See methodology.