FitMyLLM
▸ NVIDIA· BLACKWELL

RTX Pro 6000

Running LLMs on the RTX Pro 6000 — the long read: which models fit at which quantisation, and the settings worth changing. · Or what else $8,565 buys

VRAM
96 GB
FLAGSHIP
BANDWIDTH
1792
GB/S
MODELS Q4
392/449
87%
7B Q4 SPEED
~205
BLAZING
▸ MODEL COVERAGE @ Q487% OF ALL
▸ ESTIMATED SPEED· BY MODEL SIZE @ Q4

Average speeds at Q4 quantization. Actual performance varies by model architecture and context length.

3B
~478
TOK/S
7B
~205
TOK/S
14B
~102
TOK/S
32B
~45
TOK/S
70B
~20
TOK/S
▸ MEASURED RIG REPORTS

We rent the machine and time every model on it: decode, VRAM peak, concurrency, watts and cost per million tokens. Yours may already be one of them — and two are free to read in full.

SEE THE REPORTS →
▸ SPECIFICATIONS
VRAM
96 GB
BANDWIDTH
1792 GB/s
FP16 COMPUTE
209.5 TFLOPS
TDP
300W
MEMORY
GDDR7
ARCHITECTURE
Blackwell
CUDA CORES
21,760
TENSOR CORES
680
PCIE
Gen 5 x16
MSRP
$8,565
357
FAST MODELS · >30 TOK/S
Real-time chat speed
392
USABLE · >10 TOK/S
Comfortable for all tasks
392
TOTAL COMPATIBLE
Fit in VRAM at Q4
▸ RENT IT IN THE CLOUD

Buying RTX Pro 6000 costs $15–$40k and isn’t practical for most teams. Spin one up by the hour instead:

Spin up in ~60s. Pay by the second. Cancel anytime.

Some links are affiliate links — we may earn a small commission at no extra cost to you. This helps keep FitMyLLM free and independent.

▸ COMPATIBLE MODELS· 392
S
Falcon-H1R Tiny 90M0.09B
FALCON·256K CTX· CHAT· REASONING
15929
TOK/S · 1% VRAM
›
S
SmolLM2 135M0.135B
SMOLLM·2K CTX· CHAT
10619
TOK/S · 1% VRAM
›
S
nomic-embed-text-v1.5 100M0.14B
EMBEDDING·8K CTX· CHAT
10240
TOK/S · 1% VRAM
›
S
GPT-2 124M0.14B
GPT2·1K CTX· CHAT
10240
TOK/S · 1% VRAM
›
S
SmolVLM 256M0.256B
SMOLLM·8K CTX· CHAT· VISION
5600
TOK/S · 1% VRAM
›
S
Gemma 3 270M0.27B
GEMMA·32K CTX· CHAT
5310
TOK/S · 1% VRAM
›
S
Snowflake Arctic Embed M v2.00.305B
EMBEDDING·8K CTX· EMBEDDING· MULTILINGUAL
4700
TOK/S · 1% VRAM
›
S
bge-large-en-v1.5 335M0.335B
EMBEDDING·1K CTX· CHAT
4279
TOK/S · 1% VRAM
›
S
mxbai-embed-large-v10.335B
EMBEDDING·1K CTX· EMBEDDING
4279
TOK/S · 1% VRAM
›
S
Snowflake Arctic Embed L0.335B
EMBEDDING·1K CTX· EMBEDDING
4279
TOK/S · 1% VRAM
›
S
LFM2 350M0.35B
LFM·125K CTX· CHAT· TOOL_USE
4096
TOK/S · 1% VRAM
›
S
SmolLM2 360M0.36B
SMOLLM·8K CTX· CHAT
3982
TOK/S · 1% VRAM
›
S
GPT-2 Medium 345M0.38B
GPT2·1K CTX· CHAT
3773
TOK/S · 1% VRAM
›
S
Qwen 2.5 0.5B0.5B
QWEN·32K CTX· CHAT
2867
TOK/S · 1% VRAM
›
S
SmolVLM 500M0.5B
SMOLLM·8K CTX· CHAT· VISION
2867
TOK/S · 1% VRAM
›
S
Falcon-H1 0.5B0.52B
FALCON·128K CTX· CHAT
2757
TOK/S · 1% VRAM
›
S
BGE-M30.568B
EMBEDDING·8K CTX· EMBEDDING
2524
TOK/S · 1% VRAM
›
S
Snowflake Arctic Embed L v2.00.568B
EMBEDDING·8K CTX· EMBEDDING· MULTILINGUAL
2524
TOK/S · 1% VRAM
›
S
Qwen3-Embedding 0.6B0.6B
EMBEDDING·32K CTX· EMBEDDING· MULTILINGUAL
2389
TOK/S · 1% VRAM
›
S
Falcon-H1R Tiny 0.6B0.6B
FALCON·32K CTX· CHAT· REASONING
2389
TOK/S · 1% VRAM
›
S
Falcon Perception 0.6B0.6B
FALCON·4K CTX· VISION
2389
TOK/S · 1% VRAM
›
S
Qwen 1.5 0.5B0.62B
QWEN·32K CTX· CHAT
2312
TOK/S · 1% VRAM
›
S
LFM2 700M0.74B
LFM·125K CTX· CHAT· TOOL_USE
1937
TOK/S · 1% VRAM
›
S
Qwen3 0.6B0.75B
QWEN·32K CTX· CHAT· REASONING
1911
TOK/S · 1% VRAM
›
S
GPT-2 Large 774M0.81B
GPT2·1K CTX· CHAT
1770
TOK/S · 1% VRAM
›
S
Qwen 3.5 0.8B0.87B
QWEN·256K CTX· CHAT· CODING· MULTILINGUAL
1648
TOK/S · 1% VRAM
›
S
InternVL3 1B0.94B
OTHER·32K CTX· CHAT· VISION
1525
TOK/S · 1% VRAM
›
S
MiniCPM5 1B1.08B
MINICPM·128K CTX· CHAT· REASONING· MULTILINGUAL
1327
TOK/S · 1% VRAM
›
S
TinyLlama 1.1B1.1B
LLAMA·2K CTX· CHAT
1303
TOK/S · 1% VRAM
›
S
LFM2.5-1.2B-Thinking1.2B
LFM·122K CTX· CHAT· REASONING· TOOL_USE
1195
TOK/S · 1% VRAM
›
S
Llama-3.2-1B1.2B
LLAMA·4K CTX· CHAT
1195
TOK/S · 1% VRAM
›
S
LFM2 1.2B1.2B
LFM·125K CTX· CHAT· TOOL_USE· MULTILINGUAL
1195
TOK/S · 1% VRAM
›
S
Zamba2 1.2B1.2B
OTHER·4K CTX· CHAT
1195
TOK/S · 1% VRAM
›
S
EXAONE-4.0-1.2B1.3B
EXAONE·64K CTX· CHAT
1103
TOK/S · 1% VRAM
›
S
OPT 1.3B1.3B
OPT·2K CTX· CHAT
1103
TOK/S · 1% VRAM
›
S
MiniCPM-V 4.61.3B
OTHER·256K CTX· CHAT· VISION
1103
TOK/S · 1% VRAM
›
S
DeepSeek Coder 1.3B1.35B
DEEPSEEK·16K CTX· CODING
1062
TOK/S · 1% VRAM
›
S
Phi-1 1.3B1.42B
PHI·2K CTX· CODING
1010
TOK/S · 1% VRAM
›
S
Phi-1.5 1.3B1.42B
PHI·2K CTX· CHAT· CODING
1010
TOK/S · 1% VRAM
›
S
LFM2 8B A1B8.3BMoE
LFM·125K CTX· CHAT· TOOL_USE· MULTILINGUAL
956
TOK/S · 6% VRAM
›
▸ NEXT STEP

Get personalized recommendations.

See ranked models with benchmark scores, run commands, and precise speed estimates for your RTX Pro 6000.

WHAT THIS CARD IS WORTH

RTX Pro 6000 holds 392 of the models in our catalogue and is, in practice, a IQ4_XS card — the largest it takes is dots.llm1.inst 142.8B at IQ4_XS.

TOKENS/SEC PER $100
1.8
8B at Q4_K_M, so cards compare like for like
VRAM PER $100
1.12 GB
what memory costs on this card
THE BIGGEST IT TAKES
dots.llm1.inst 142.8B142.8B · IQ4_XS86.0 GB9 tok/sEST
WizardLM 2 8x22B141B · Q4_K_S85.7 GB31 tok/sEST
Mixtral-8x22B140.6B · Q4_K_S85.5 GB31 tok/sEST
DBRX 132B132B · Q4_K_M83.8 GB32 tok/sEST
Mistral Medium 3.5128B · Q4_K_M82.1 GB9 tok/sEST
Pixtral Large 124B124B · Q4_K_M79.7 GB9 tok/sEST
Nemotron 3 Super 120B-A12B123.61B · Q4_K_M78.4 GB96 tok/sEST
Mistral-Large 123B123B · Q4_K_M79.1 GB9 tok/sEST
AGAINST CARDS OF SIMILAR MEMORY
Radeon Instinct MI300128 GB$12,0005.8 tok/s per $100
Radeon Instinct MI250128 GB$12,0002.9 tok/s per $100
Instinct MI250X128 GB$10,0003.5 tok/s per $100
M1 Ultra (128GB)96 GB$4,9991.4 tok/s per $100
RTX Pro 600096 GB$8,5651.8 tok/s per $100

Neighbours in memory rather than in price: memory decides whether a card can do the job at all, so two cards of the same size at different prices is the comparison you are making. Ordered by memory, then bandwidth — not by the value column, which is worked out from bandwidth and price alone and therefore rewards a cheap card whatever its software stack does to that bandwidth in practice. Read it as one input, not as a ranking.

▸ DEVICE UNDER TEST

RTX Pro 6000 — 96 GB VRAM.

▸ RTX PRO 6000 SPEC
BRAND
NVIDIA
VRAM
96 GB GDDR7
BANDWIDTH
1792 GB/s
FP16 COMPUTE
209.5 TFLOPS
FP32 COMPUTE
104.8 TFLOPS
CUDA CORES
21,760
TENSOR CORES
680
TDP
300 W
ARCHITECTURE
Blackwell
MSRP
$8565
▸ AI CAPABILITY
392/ 449 models @ Q4

With 96 GB VRAM and 1792 GB/s bandwidth, this GPU handles models up to 132B parameters.

Speed ≈ bandwidth / model_size × efficiency. A 7B model at Q4 runs at ~205 tok/s.

RENT IT — LIVE PRICES
Checking what the clouds are charging…
§ 01TOP MODELS FOR RTX PRO 6000
392 FIT · SHOWING 20
MODELSIZEVRAM Q4TOK/SAVG
DBRX 132B132B81.2 GB4046.3
Mistral Medium 3.5128B78.7 GB1146.6
Pixtral Large 124B124B76.3 GB1239.3
Nemotron 3 Super 120B-A12B123.61B76.0 GB11953.2
Mistral-Large 123B123B75.7 GB1233.5
Devstral 2 123B123B75.7 GB1238.1
Qwen 3.5 122B A10B122B75.1 GB14356.8
Nemotron 3 Super 120B120B73.8 GB11957.3
Mistral Small 4 119B119B73.2 GB22150.2
GPT-OSS 120B117B72.0 GB28154.1
Command A 111B111B68.3 GB1327.6
GLM 4.5 Air110B67.7 GB11951.0
Qwen 1.5 110B110B67.7 GB1333.4
Llama 4 Scout 17B-16E109B67.1 GB8433.9
Cogito v2 109B MoE109B67.1 GB84—
Ling 2.6 Flash107.49B66.2 GB19436.8
Sarvam 105B105B64.7 GB1448.0
Command-R+ 104B104B64.1 GB1452.7
Llama-3.2-90B-Vision-Instruct90B55.5 GB1648.5
Hunyuan A13B80B49.4 GB11081.1