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Louer Nvidia B300 MIG 34GB.

Name: Nvidia B300 MIG 34GB
Brand: Nvidia
SKU: nvidia-b300-mig-34gb

Blackwell 34GB VRAM

AI models

Models that run on this GPU.

GPU-count + quantization recommendations covering fine-tuning, inference, and run-it-yourself scenarios on the Nvidia B300 MIG 34GB.

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FAQ

AI models on this GPU.

What AI models can I run on a Nvidia B300 MIG 34GB?

The grid above lists every open-weights model with a recommended GPU configuration for this card. Each row tells you the minimum GPU count and the quantization level (FP16, FP8, INT8, INT4) needed to load the model in 34GB of VRAM.

What's the VRAM minimum to run a model on the Nvidia B300 MIG 34GB?

Rule of thumb: a model needs roughly (parameters × bytes-per-weight × 1.2) of VRAM to load, plus headroom for the KV cache during inference. FP16 = 2 bytes/weight, FP8/INT8 = 1 byte, INT4 = 0.5 bytes. A 70B model at FP16 needs ~168GB; at INT4 it drops to ~42GB and fits a single high-VRAM card.

How does quantization (FP16 vs FP8 vs INT4) affect what fits?

Lower-precision quantization shrinks the memory footprint nearly linearly with the bit count. The trade-off is output quality: FP16 is the reference, FP8 is usually indistinguishable for most prompts, INT8 introduces small quality losses, INT4 is noticeably degraded on reasoning-heavy tasks but fine for chat. The badge on each row tells you which level the recommendation assumes.

Can I fine-tune on the Nvidia B300 MIG 34GB or only do inference?

Fine-tuning needs 4–8× more VRAM than inference at the same model size — gradients, optimizer state, and activations all live in memory. LoRA / QLoRA cut that overhead dramatically (often 4–10×). The notes column flags whether a row is an inference-only recommendation or includes a fine-tuning path.

Where do these GPU-count recommendations come from?

We curate them from official model cards, community benchmark threads (r/LocalLLaMA, HuggingFace forum), and known-good configurations published by the model makers. Each recommendation has been verified to load at the stated quantization on the listed GPU count — though throughput and context-length still vary by workload.

Louer Nvidia B300 MIG 34GB.

Daily median across providers.

All providers carrying this GPU.

Run these on this GPU.

Frequently asked.

Models that run on this GPU.

nim/nvidia/llama-3.3-nemotron-super-49b-v1

NVIDIA: Llama 3.3 Nemotron Super 49B V1.5

LLaVA 13B

Code Llama 13B

Baichuan2-13B

ReMM SLERP 13B

MythoMax 13B

TheDrummer: Skyfall 36B V2

Qwen: Qwen3.5-35B-A3B

Qwen3.6 35B A3b Fp8

Qwen: Qwen3.6 35B A3B

Gemma 3 27B

Gemma 2 27B

Qwen: Qwen3.6 27B

Qwen: Qwen3.5-27B

Gemma 3 27B It

Gemma 3 27B Pt

Medgemma 27B Text It

Gemma 3 27B It Lora

Qwen3.5 27B Lora

Qwen3.6 27B Lora

Ternary Bonsai 27B

Qwen: Qwen3.8 27B

AI models on this GPU.