NVIDIA · Blackwell Ultra
Best AI Models for NVIDIA B300 (288 GB)
Runs everything up to 120B MoE well.
Datacenter Blackwell Ultra — rack/cloud only, not a desktop card. Listed for comparison.
| # | Model | Speed | llmrun Score | Quant · VRAM |
|---|---|---|---|---|
| 1 | Q4_K_M · 186.5 GB · 229 t/s | 229 tok/s | Q4_K_M · 186.5 GB | |
| 2 | DeepSeek V4 Flash 0731DeepSeek Q4_K_M · 183.0 GB · 181 t/s | 181 tok/s | Q4_K_M · 183.0 GB | |
| 3 | GLM 5.3 FlashZ.ai Q4_K_M · 205.2 GB · 217 t/s | 217 tok/s | Q4_K_M · 205.2 GB | |
| 4 | Qwen3.8 27BAlibaba Q4_K_M · 17.9 GB · 299 t/s | 299 tok/s | Q4_K_M · 17.9 GB | |
| 5 | Hy3Tencent Q4_K_M · 182.3 GB · 147 t/s | 147 tok/s | Q4_K_M · 182.3 GB |
| # | Model | Speed | Coding Score | Quant · VRAM |
|---|---|---|---|---|
| 1 | Q4_K_M · 186.5 GB · 229 t/s | 229 tok/s | Q4_K_M · 186.5 GB | |
| 2 | DeepSeek V4 Flash 0731DeepSeek Q4_K_M · 183.0 GB · 181 t/s | 181 tok/s | Q4_K_M · 183.0 GB | |
| 3 | Qwen3.8 27BAlibaba Q4_K_M · 17.9 GB · 299 t/s | 299 tok/s | Q4_K_M · 17.9 GB | |
| 4 | GLM 5.3 FlashZ.ai Q4_K_M · 205.2 GB · 217 t/s | 217 tok/s | Q4_K_M · 205.2 GB | |
| 5 | Hy3Tencent Q4_K_M · 182.3 GB · 147 t/s | 147 tok/s | Q4_K_M · 182.3 GB |
| # | Model | Speed | Reasoning Score | Quant · VRAM |
|---|---|---|---|---|
| 1 | Q4_K_M · 183.0 GB · 181 t/s | 181 tok/s | Q4_K_M · 183.0 GB | |
| 2 | GLM 5.3 FlashZ.ai Q4_K_M · 205.2 GB · 217 t/s | 217 tok/s | Q4_K_M · 205.2 GB | |
| 3 | Qwen3.8 27BAlibaba Q4_K_M · 17.9 GB · 299 t/s | 299 tok/s | Q4_K_M · 17.9 GB | |
| 4 | Inkling SmallThinking Machines Q4_K_M · 162.7 GB · 399 t/s | 399 tok/s | Q4_K_M · 162.7 GB | |
| 5 | Hy3Tencent Q4_K_M · 182.3 GB · 147 t/s | 147 tok/s | Q4_K_M · 182.3 GB |
| # | Model | Speed ↓ | llmrun Score | Quant · VRAM |
|---|---|---|---|---|
| 1 | Qwen3.5 4BAlibabaHow to run → Q4_K_M · 3.4 GB · 1595 t/s | 1595 tok/s | Q4_K_M · 3.4 GB | |
| 2 | Qwen3.5 9BAlibaba Q4_K_M · 6.6 GB · 818 t/s | 818 tok/s | Q4_K_M · 6.6 GB | |
| 3 | GPT OSS 20BOpenAI Q4_K_M · 13.1 GB · 550 t/s | 550 tok/s | Q4_K_M · 13.1 GB | |
| 4 | Gemma 4 26B A4B ITGoogle Q4_K_M · 16.5 GB · 459 t/s | 459 tok/s | Q4_K_M · 16.5 GB | |
| 5 | Hy3Tencent Q4_K_M · 182.3 GB · 147 t/s | 147 tok/s | Q4_K_M · 182.3 GB |
| # | Model | Speed | Vision Score | Quant · VRAM |
|---|---|---|---|---|
| 1 | Q4_K_M · 205.2 GB · 217 t/s | 217 tok/s | Q4_K_M · 205.2 GB | |
| 2 | Qwen3.8 27BAlibaba Q4_K_M · 17.9 GB · 299 t/s | 299 tok/s | Q4_K_M · 17.9 GB | |
| 3 | Inkling SmallThinking Machines Q4_K_M · 162.7 GB · 399 t/s | 399 tok/s | Q4_K_M · 162.7 GB | |
| 4 | MiniMax M3MiniMax Q4_K_M · 258.0 GB · 179 t/s | 179 tok/s | Q4_K_M · 258.0 GB | |
| 5 | Qwen3.8 Flash NextAlibaba Q4_K_M · 109.0 GB · 102 t/s | 102 tok/s | Q4_K_M · 109.0 GB |
The B300 runs everything up to 120B MoE well. Blackwell Ultra generation, released 2025.
B300 strengths and weaknesses
Strengths
- Runs 120B MoE models: GPT OSS 120B at 378 tok/s in 70.8 GB
- Room for long context: Llama 3.3 70B Instruct at Q4 uses 51.3 GB, leaving 236.7 GB free
- Reads long prompts fast: A 4K-token prompt on MiMo V2.6 Flash RL starts answering in 82 ms
- FP8 and NVFP4 run natively: Blackwell takes FP8 and NVFP4 checkpoints in vLLM as published
Weaknesses
- 1400 W under load: Plan a 2,800 W PSU; ≈$307 a year at 4 h a day
Output speed depends on memory bandwidth (8000 GB/s).
- 9BQwen3.5 9B · Q4_K_M · 6.6 GB818tok/s
- 14BQwen3 14B · Q4_K_M · 11.9 GB547tok/s
- 27–31BQwen3.8 27B · Q4_K_M · 17.9 GB299tok/s
- 35B MoEQwen3.6 35B A3B · Q4_K_M · 22.0 GB363tok/s
- 70BLlama 3.3 70B Instruct · Q4_K_M · 51.3 GB112tok/s
- 120B MoEGPT OSS 120B · Q4_K_M · 70.8 GB378tok/s
Estimated speeds: Q4_K_M, 4K context, one user. How we estimate
All 433 models on the B300
Featured onlyBest quant that fits, ordered by llmrun Score. Fit grades how well it runs here, S best. How ranking works
| Model | Quant | VRAM | Speed | Context | Score | Fit |
|---|---|---|---|---|---|---|
FrogNano 4B 2609ChatFunctions | Q4_K_M | 3.4 GB | 1595.1 t/s | 262K | S100, Runs great | |
Ling 3.0 Flash VLVisionFunctions | Q4_K_M | 76 GB | 332.6 t/s | 131K | S100, Runs great | |
Qwen3 VL 235B A22B ThinkingVisionFunctions | Q4_K_M | 143.3 GB | 128.1 t/s | 262K | S95, Runs great | |
Unlimited OCRVision | Q4_K_M | 3.3 GB | 1219.8 t/s | 33K | S100, Runs great | |
SenseNova Loop 9B PreviewVisionChatFunctions | Q4_K_M | 8.2 GB | 817.6 t/s | 262K | S100, Runs great | |
D1 2BVisionFunctions | Q4_K_M | 2.3 GB | 3354.8 t/s | 128K | S100, Runs great | |
| Q4_K_M | 77.0 GB | 208.4 t/s | — | S100, Runs great | ||
Llm Jp 4.1 8B ThinkingChatFunctions | Q4_K_M | 7.6 GB | 909.1 t/s | 66K | S100, Runs great | |
Command A Plus 05 2026 BF16VisionChatFunctions | Q4_K_M | 132.1 GB | 212.4 t/s | 200K | S100, Runs great | |
Kolibri 1 BF16ChatReasoningFunctions | Q4_K_M | 47.9 GB | 317.2 t/s | 262K | S100, Runs great | |
MiniCPM V 4.6VisionFunctions | Q4_K_M | 1.5 GB | 4601.8 t/s | 262K | S100, Runs great | |
AesCode 8BVisionCodeFunctions | Q4_K_M | 8.0 GB | 887.4 t/s | 262K | S100, Runs great | |
Ornith 1.5 35B A3BChatFunctions | Q4_K_M | 22.0 GB | 362.7 t/s | 262K | S100, Runs great | |
AREX 2VisionFunctionsReasoning | Q4_K_M | 17.6 GB | 303.0 t/s | 262K | S100, Runs great | |
AesCode 32BVisionCodeFunctions | Q4_K_M | 23 GB | 251.8 t/s | 262K | S100, Runs great |
Rent NVIDIA B300 in the cloud
Hourly rate on demand for one B300.
RunPod$5+ bonus credit
from$6.94/hr
Cost per million tokens
Output-token cost on a B300 rented at $6.94/hr, one request at a time. Batch several users on the same card and the cost per token drops several-fold.
| Model | Quant | Speed | Per 1M output |
|---|---|---|---|
| Inkling Small | 399 tok/s | $4.84$0.039 input | |
| MiMo V2.6 Flash RL | 229 tok/s | $8.43$0.039 input | |
| GLM 5.3 Flash | 217 tok/s | $8.89$0.042 input | |
| DeepSeek V4 Flash 0731 | 181 tok/s | $10.66$0.063 input | |
| Hy3 | 147 tok/s | $13.16$0.048 input |
Specs
- Architecture
- Blackwell Ultra
- VRAM
- 288 GB HBM3e
- Memory bandwidth
- 8000.0 GB/s
- FP16 (dense)
- 3750.00 TFLOPS
- CUDA cores
- 20,480
- Tensor cores
- 640
- Compute capability
- 10.0
- TDP
- 1400 W
- Released
- 2025-08-01
B300 FAQ
What is the largest model the B300 can run?
Beam 1.0 501B A23B (501.3B) is the largest at 4-bit or better: at Q4_K_S it uses 285.2 GB of 288 GB, and runs at about 185 tok/s.
Can the B300 run MiMo V2.6 Flash RL?
Yes. MiMo V2.6 Flash RL fits at Q4_K_M, using 186.5 GB of 288 GB, and it is the best model that runs well on this card.
How many tokens per second does the B300 give?
About 229 tok/s on MiMo V2.6 Flash RL at Q4_K_M, with the first token after 0.1 s on a 4K-token prompt.
What power supply does the B300 need?
Plan a 2800 W PSU (2× the 1400 W TDP).
Is 288 GB enough for coding and agents?
Yes for coding: MiMo V2.6 Flash RL, the best of the 25 coding models that fit, runs at about 229 tok/s.