FitMyLLM
NVIDIA· HOPPER

NVIDIA H200 SXM 141GB

Running LLMs on the H200 SXM 141GB — the long read: which models fit at which quantisation, and the settings worth changing. · Or what else $30,000 buys

VRAM
140 GB
FLAGSHIP
BANDWIDTH
4800
GB/S
MODELS Q4
397/449
88%
7B Q4 SPEED
~549
BLAZING
▸ MODEL COVERAGE @ Q488% OF ALL
▸ ESTIMATED SPEED· BY MODEL SIZE @ Q4

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

3B
~1280
TOK/S
7B
~549
TOK/S
14B
~274
TOK/S
32B
~120
TOK/S
70B
~55
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
140 GB
BANDWIDTH
4800 GB/s
FP16 COMPUTE
1979 TFLOPS
TDP
700W
MEMORY
HBM3e
ARCHITECTURE
Hopper
CUDA CORES
16,896
TENSOR CORES
528
PCIE
Gen 5 x16
MSRP
$30,000
394
FAST MODELS · >30 TOK/S
Real-time chat speed
397
USABLE · >10 TOK/S
Comfortable for all tasks
397
TOTAL COMPATIBLE
Fit in VRAM at Q4
▸ RENT IT IN THE CLOUD

Buying H200 SXM 141GB 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· 397
S
Falcon-H1R Tiny 90M0.09B
FALCON·256K CTX· CHAT· REASONING
42667
TOK/S · 0% VRAM
S
SmolLM2 135M0.135B
SMOLLM·2K CTX· CHAT
28444
TOK/S · 0% VRAM
S
nomic-embed-text-v1.5 100M0.14B
EMBEDDING·8K CTX· CHAT
27429
TOK/S · 0% VRAM
S
GPT-2 124M0.14B
GPT2·1K CTX· CHAT
27429
TOK/S · 0% VRAM
S
SmolVLM 256M0.256B
SMOLLM·8K CTX· CHAT· VISION
15000
TOK/S · 0% VRAM
S
Gemma 3 270M0.27B
GEMMA·32K CTX· CHAT
14222
TOK/S · 0% VRAM
S
Snowflake Arctic Embed M v2.00.305B
EMBEDDING·8K CTX· EMBEDDING· MULTILINGUAL
12590
TOK/S · 0% VRAM
S
bge-large-en-v1.5 335M0.335B
EMBEDDING·1K CTX· CHAT
11463
TOK/S · 0% VRAM
S
mxbai-embed-large-v10.335B
EMBEDDING·1K CTX· EMBEDDING
11463
TOK/S · 0% VRAM
S
Snowflake Arctic Embed L0.335B
EMBEDDING·1K CTX· EMBEDDING
11463
TOK/S · 0% VRAM
S
LFM2 350M0.35B
LFM·125K CTX· CHAT· TOOL_USE
10971
TOK/S · 1% VRAM
S
SmolLM2 360M0.36B
SMOLLM·8K CTX· CHAT
10667
TOK/S · 1% VRAM
S
GPT-2 Medium 345M0.38B
GPT2·1K CTX· CHAT
10105
TOK/S · 1% VRAM
S
Qwen 2.5 0.5B0.5B
QWEN·32K CTX· CHAT
7680
TOK/S · 1% VRAM
S
SmolVLM 500M0.5B
SMOLLM·8K CTX· CHAT· VISION
7680
TOK/S · 1% VRAM
S
Falcon-H1 0.5B0.52B
FALCON·128K CTX· CHAT
7385
TOK/S · 1% VRAM
S
BGE-M30.568B
EMBEDDING·8K CTX· EMBEDDING
6761
TOK/S · 1% VRAM
S
Snowflake Arctic Embed L v2.00.568B
EMBEDDING·8K CTX· EMBEDDING· MULTILINGUAL
6761
TOK/S · 1% VRAM
S
Qwen3-Embedding 0.6B0.6B
EMBEDDING·32K CTX· EMBEDDING· MULTILINGUAL
6400
TOK/S · 1% VRAM
S
Falcon-H1R Tiny 0.6B0.6B
FALCON·32K CTX· CHAT· REASONING
6400
TOK/S · 1% VRAM
S
Falcon Perception 0.6B0.6B
FALCON·4K CTX· VISION
6400
TOK/S · 1% VRAM
S
Qwen 1.5 0.5B0.62B
QWEN·32K CTX· CHAT
6194
TOK/S · 1% VRAM
S
LFM2 700M0.74B
LFM·125K CTX· CHAT· TOOL_USE
5189
TOK/S · 1% VRAM
S
Qwen3 0.6B0.75B
QWEN·32K CTX· CHAT· REASONING
5120
TOK/S · 1% VRAM
S
GPT-2 Large 774M0.81B
GPT2·1K CTX· CHAT
4741
TOK/S · 1% VRAM
S
Qwen 3.5 0.8B0.87B
QWEN·256K CTX· CHAT· CODING· MULTILINGUAL
4414
TOK/S · 1% VRAM
S
InternVL3 1B0.94B
OTHER·32K CTX· CHAT· VISION
4085
TOK/S · 1% VRAM
S
MiniCPM5 1B1.08B
MINICPM·128K CTX· CHAT· REASONING· MULTILINGUAL
3556
TOK/S · 1% VRAM
S
TinyLlama 1.1B1.1B
LLAMA·2K CTX· CHAT
3491
TOK/S · 1% VRAM
S
LFM2.5-1.2B-Thinking1.2B
LFM·122K CTX· CHAT· REASONING· TOOL_USE
3200
TOK/S · 1% VRAM
S
Llama-3.2-1B1.2B
LLAMA·4K CTX· CHAT
3200
TOK/S · 1% VRAM
S
LFM2 1.2B1.2B
LFM·125K CTX· CHAT· TOOL_USE· MULTILINGUAL
3200
TOK/S · 1% VRAM
S
Zamba2 1.2B1.2B
OTHER·4K CTX· CHAT
3200
TOK/S · 1% VRAM
S
EXAONE-4.0-1.2B1.3B
EXAONE·64K CTX· CHAT
2954
TOK/S · 1% VRAM
S
OPT 1.3B1.3B
OPT·2K CTX· CHAT
2954
TOK/S · 1% VRAM
S
MiniCPM-V 4.61.3B
OTHER·256K CTX· CHAT· VISION
2954
TOK/S · 1% VRAM
S
DeepSeek Coder 1.3B1.35B
DEEPSEEK·16K CTX· CODING
2844
TOK/S · 1% VRAM
S
Phi-1 1.3B1.42B
PHI·2K CTX· CODING
2704
TOK/S · 1% VRAM
S
Phi-1.5 1.3B1.42B
PHI·2K CTX· CHAT· CODING
2704
TOK/S · 1% VRAM
S
LFM2 8B A1B8.3BMoE
LFM·125K CTX· CHAT· TOOL_USE· MULTILINGUAL
2560
TOK/S · 4% VRAM
▸ NEXT STEP

Get personalized recommendations.

See ranked models with benchmark scores, run commands, and precise speed estimates for your H200 SXM 141GB.

WHAT THIS CARD IS WORTH

H200 SXM 141GB holds 397 of the models in our catalogue and is, in practice, a IQ4_XS card — the largest it takes is Command A+ at IQ4_XS.

TOKENS/SEC PER $100
0.1
8B at Q4_K_M, so cards compare like for like
VRAM PER $100
0.47 GB
what memory costs on this card
THE BIGGEST IT TAKES
Command A+218B · IQ4_XS124.5 GB10 tok/sEST
Step 3.7 Flash201.37B · Q4_K_M125.8 GB21 tok/sEST
Falcon 180B180B · Q4_K_M113.8 GB1 tok/sEST
bloom 176.2B176.2B · Q4_K_M125.5 GB1 tok/sEST
dots.llm1.inst 142.8B142.8B · Q6_K123.5 GB1 tok/sEST
WizardLM 2 8x22B141B · Q6_K119.0 GB5 tok/sEST
Mixtral-8x22B140.6B · Q6_K118.7 GB4 tok/sEST
DBRX 132B132B · Q6_K111.4 GB5 tok/sEST
AGAINST CARDS OF SIMILAR MEMORY
M4 Ultra (192GB)144 GB$7,4991.2 tok/s per $100
M2 Ultra (192GB)144 GB$5,4991.3 tok/s per $100
M3 Ultra (192GB)144 GB$6,9991.0 tok/s per $100
B300144 GB$35,0000.1 tok/s per $100
H200 SXM 141GB140 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 H200 SXM 141GB — 140 GB VRAM.

H200 SXM 141GB SPEC
BRAND
NVIDIA
VRAM
140 GB HBM3e
BANDWIDTH
4800 GB/s
FP16 COMPUTE
1979 TFLOPS
FP32 COMPUTE
67 TFLOPS
CUDA CORES
16,896
TENSOR CORES
528
TDP
700 W
ARCHITECTURE
Hopper
MSRP
$30000
▸ AI CAPABILITY
397/ 449 models @ Q4

With 140 GB VRAM and 4800 GB/s bandwidth, this GPU handles models up to 180B parameters.

Speed ≈ bandwidth / model_size × efficiency. A 7B model at Q4 runs at ~549 tok/s.

RENT IT — LIVE PRICES
Checking what the clouds are charging…
§ 01TOP MODELS FOR H200 SXM 141GB
397 FIT · SHOWING 20
MODELSIZEVRAM Q4TOK/SAVG
Falcon 180B180B110.5 GB2151.3
bloom 176.2B176.2B108.2 GB2215.0
dots.llm1.inst 142.8B142.8B87.8 GB27
WizardLM 2 8x22B141B86.7 GB9842.4
Mixtral-8x22B140.6B86.4 GB9831.9
DBRX 132B132B81.2 GB10746.3
Mistral Medium 3.5128B78.7 GB3046.6
Pixtral Large 124B124B76.3 GB3139.3
Nemotron 3 Super 120B-A12B123.61B76.0 GB32053.2
Mistral-Large 123B123B75.7 GB3133.5
Devstral 2 123B123B75.7 GB3138.1
Qwen 3.5 122B A10B122B75.1 GB38456.8
Nemotron 3 Super 120B120B73.8 GB32057.3
Mistral Small 4 119B119B73.2 GB59150.2
GPT-OSS 120B117B72.0 GB75354.1
Command A 111B111B68.3 GB3527.6
GLM 4.5 Air110B67.7 GB32051.0
Qwen 1.5 110B110B67.7 GB3533.4
Llama 4 Scout 17B-16E109B67.1 GB22633.9
Cogito v2 109B MoE109B67.1 GB226