FitMyLLM
NVIDIA· HOPPER

NVIDIA H100 NVL 94 GB

Running LLMs on the H100 NVL 94 GB — the long read: which models fit at which quantisation, and the settings worth changing. · Or what else $30,000 buys

VRAM
94 GB
FLAGSHIP
BANDWIDTH
3940
GB/S
MODELS Q4
392/449
87%
7B Q4 SPEED
~450
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
~1051
TOK/S
7B
~450
TOK/S
14B
~225
TOK/S
32B
~99
TOK/S
70B
~45
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
94 GB
BANDWIDTH
3940 GB/s
FP16 COMPUTE
241.3 TFLOPS
TDP
400W
MEMORY
HBM3
ARCHITECTURE
Hopper
CUDA CORES
16,896
TENSOR CORES
528
PCIE
Gen 5 x16
MSRP
$30,000
386
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 H100 NVL 94 GB 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.

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▸ COMPATIBLE MODELS· 392
S
Falcon-H1R Tiny 90M0.09B
FALCON·256K CTX· CHAT· REASONING
35022
TOK/S · 1% VRAM
S
SmolLM2 135M0.135B
SMOLLM·2K CTX· CHAT
23348
TOK/S · 1% VRAM
S
nomic-embed-text-v1.5 100M0.14B
EMBEDDING·8K CTX· CHAT
22514
TOK/S · 1% VRAM
S
GPT-2 124M0.14B
GPT2·1K CTX· CHAT
22514
TOK/S · 1% VRAM
S
SmolVLM 256M0.256B
SMOLLM·8K CTX· CHAT· VISION
12313
TOK/S · 1% VRAM
S
Gemma 3 270M0.27B
GEMMA·32K CTX· CHAT
11674
TOK/S · 1% VRAM
S
Snowflake Arctic Embed M v2.00.305B
EMBEDDING·8K CTX· EMBEDDING· MULTILINGUAL
10334
TOK/S · 1% VRAM
S
bge-large-en-v1.5 335M0.335B
EMBEDDING·1K CTX· CHAT
9409
TOK/S · 1% VRAM
S
mxbai-embed-large-v10.335B
EMBEDDING·1K CTX· EMBEDDING
9409
TOK/S · 1% VRAM
S
Snowflake Arctic Embed L0.335B
EMBEDDING·1K CTX· EMBEDDING
9409
TOK/S · 1% VRAM
S
LFM2 350M0.35B
LFM·125K CTX· CHAT· TOOL_USE
9006
TOK/S · 1% VRAM
S
SmolLM2 360M0.36B
SMOLLM·8K CTX· CHAT
8756
TOK/S · 1% VRAM
S
GPT-2 Medium 345M0.38B
GPT2·1K CTX· CHAT
8295
TOK/S · 1% VRAM
S
Qwen 2.5 0.5B0.5B
QWEN·32K CTX· CHAT
6304
TOK/S · 1% VRAM
S
SmolVLM 500M0.5B
SMOLLM·8K CTX· CHAT· VISION
6304
TOK/S · 1% VRAM
S
Falcon-H1 0.5B0.52B
FALCON·128K CTX· CHAT
6062
TOK/S · 1% VRAM
S
BGE-M30.568B
EMBEDDING·8K CTX· EMBEDDING
5549
TOK/S · 1% VRAM
S
Snowflake Arctic Embed L v2.00.568B
EMBEDDING·8K CTX· EMBEDDING· MULTILINGUAL
5549
TOK/S · 1% VRAM
S
Qwen3-Embedding 0.6B0.6B
EMBEDDING·32K CTX· EMBEDDING· MULTILINGUAL
5253
TOK/S · 1% VRAM
S
Falcon-H1R Tiny 0.6B0.6B
FALCON·32K CTX· CHAT· REASONING
5253
TOK/S · 1% VRAM
S
Falcon Perception 0.6B0.6B
FALCON·4K CTX· VISION
5253
TOK/S · 1% VRAM
S
Qwen 1.5 0.5B0.62B
QWEN·32K CTX· CHAT
5084
TOK/S · 1% VRAM
S
LFM2 700M0.74B
LFM·125K CTX· CHAT· TOOL_USE
4259
TOK/S · 1% VRAM
S
Qwen3 0.6B0.75B
QWEN·32K CTX· CHAT· REASONING
4203
TOK/S · 1% VRAM
S
GPT-2 Large 774M0.81B
GPT2·1K CTX· CHAT
3891
TOK/S · 1% VRAM
S
Qwen 3.5 0.8B0.87B
QWEN·256K CTX· CHAT· CODING· MULTILINGUAL
3623
TOK/S · 1% VRAM
S
InternVL3 1B0.94B
OTHER·32K CTX· CHAT· VISION
3353
TOK/S · 1% VRAM
S
MiniCPM5 1B1.08B
MINICPM·128K CTX· CHAT· REASONING· MULTILINGUAL
2919
TOK/S · 1% VRAM
S
TinyLlama 1.1B1.1B
LLAMA·2K CTX· CHAT
2865
TOK/S · 1% VRAM
S
LFM2.5-1.2B-Thinking1.2B
LFM·122K CTX· CHAT· REASONING· TOOL_USE
2627
TOK/S · 1% VRAM
S
Llama-3.2-1B1.2B
LLAMA·4K CTX· CHAT
2627
TOK/S · 1% VRAM
S
LFM2 1.2B1.2B
LFM·125K CTX· CHAT· TOOL_USE· MULTILINGUAL
2627
TOK/S · 1% VRAM
S
Zamba2 1.2B1.2B
OTHER·4K CTX· CHAT
2627
TOK/S · 1% VRAM
S
EXAONE-4.0-1.2B1.3B
EXAONE·64K CTX· CHAT
2425
TOK/S · 1% VRAM
S
OPT 1.3B1.3B
OPT·2K CTX· CHAT
2425
TOK/S · 1% VRAM
S
MiniCPM-V 4.61.3B
OTHER·256K CTX· CHAT· VISION
2425
TOK/S · 1% VRAM
S
DeepSeek Coder 1.3B1.35B
DEEPSEEK·16K CTX· CODING
2335
TOK/S · 1% VRAM
S
Phi-1 1.3B1.42B
PHI·2K CTX· CODING
2220
TOK/S · 1% VRAM
S
Phi-1.5 1.3B1.42B
PHI·2K CTX· CHAT· CODING
2220
TOK/S · 1% VRAM
S
LFM2 8B A1B8.3BMoE
LFM·125K CTX· CHAT· TOOL_USE· MULTILINGUAL
2101
TOK/S · 6% VRAM
▸ NEXT STEP

Get personalized recommendations.

See ranked models with benchmark scores, run commands, and precise speed estimates for your H100 NVL 94 GB.

WHAT THIS CARD IS WORTH

H100 NVL 94 GB holds 392 of the models in our catalogue and is, in practice, a IQ4_XS card — the largest it takes is WizardLM 2 8x22B at IQ4_XS.

TOKENS/SEC PER $100
0.1
8B at Q4_K_M, so cards compare like for like
VRAM PER $100
0.31 GB
what memory costs on this card
THE BIGGEST IT TAKES
WizardLM 2 8x22B141B · IQ4_XS82.0 GB8 tok/sEST
Mixtral-8x22B140.6B · IQ4_XS81.8 GB8 tok/sEST
DBRX 132B132B · Q4_K_M83.8 GB8 tok/sEST
Mistral Medium 3.5128B · Q4_K_M82.1 GB2 tok/sEST
Pixtral Large 124B124B · Q4_K_M79.7 GB2 tok/sEST
Nemotron 3 Super 120B-A12B123.61B · Q4_K_M78.4 GB23 tok/sEST
Mistral-Large 123B123B · Q4_K_M79.1 GB2 tok/sEST
Devstral 2 123B123B · Q4_K_M79.1 GB2 tok/sEST
AGAINST CARDS OF SIMILAR MEMORY
M1 Ultra (128GB)96 GB$4,9991.4 tok/s per $100
M2 Ultra (128GB)96 GB$3,9991.8 tok/s per $100
M4 Max (128GB)96 GB$3,9991.4 tok/s per $100
Instinct MI300A120 GB$12,0004.7 tok/s per $100
H100 NVL 94 GB94 GB$30,0000.1 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

NVIDIA H100 NVL 94 GB — 94 GB VRAM.

H100 NVL 94 GB SPEC
BRAND
NVIDIA
VRAM
94 GB HBM3
BANDWIDTH
3940 GB/s
FP16 COMPUTE
241.3 TFLOPS
FP32 COMPUTE
60.3 TFLOPS
CUDA CORES
16,896
TENSOR CORES
528
TDP
400 W
ARCHITECTURE
Hopper
MSRP
$30000
▸ AI CAPABILITY
392/ 449 models @ Q4

With 94 GB VRAM and 3940 GB/s bandwidth, this GPU handles models up to 132B parameters.

Speed ≈ bandwidth / model_size × efficiency. A 7B model at Q4 runs at ~450 tok/s.

RENT IT — LIVE PRICES
Checking what the clouds are charging…
§ 01TOP MODELS FOR H100 NVL 94 GB
392 FIT · SHOWING 20
MODELSIZEVRAM Q4TOK/SAVG
DBRX 132B132B81.2 GB8846.3
Mistral Medium 3.5128B78.7 GB2546.6
Pixtral Large 124B124B76.3 GB2539.3
Nemotron 3 Super 120B-A12B123.61B76.0 GB26353.2
Mistral-Large 123B123B75.7 GB2633.5
Devstral 2 123B123B75.7 GB2638.1
Qwen 3.5 122B A10B122B75.1 GB31556.8
Nemotron 3 Super 120B120B73.8 GB26357.3
Mistral Small 4 119B119B73.2 GB48550.2
GPT-OSS 120B117B72.0 GB61854.1
Command A 111B111B68.3 GB2827.6
GLM 4.5 Air110B67.7 GB26351.0
Qwen 1.5 110B110B67.7 GB2933.4
Llama 4 Scout 17B-16E109B67.1 GB18533.9
Cogito v2 109B MoE109B67.1 GB185
Ling 2.6 Flash107.49B66.2 GB42636.8
Sarvam 105B105B64.7 GB3048.0
Command-R+ 104B104B64.1 GB3052.7
Llama-3.2-90B-Vision-Instruct90B55.5 GB3548.5
Hunyuan A13B80B49.4 GB24281.1