FitMyLLM
INTEL· GENERATION 12.5

Intel Data Center GPU Max 1350

Running LLMs on the Data Center GPU Max 1350 — the long read: which models fit at which quantisation, and the settings worth changing. · Or what a budget buys

VRAM
96 GB
FLAGSHIP
BANDWIDTH
2460
GB/S
MODELS Q4
392/449
87%
7B Q4 SPEED
~112
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
~262
TOK/S
7B
~112
TOK/S
14B
~56
TOK/S
32B
~25
TOK/S
70B
~11
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
2460 GB/s
FP16 COMPUTE
44.4 TFLOPS
TDP
450W
MEMORY
HBM2e
ARCHITECTURE
Generation 12.5
COMPUTE UNITS
896
PCIE
Gen 5 x16
309
FAST MODELS · >30 TOK/S
Real-time chat speed
383
USABLE · >10 TOK/S
Comfortable for all tasks
392
TOTAL COMPATIBLE
Fit in VRAM at Q4
▸ RENT IT IN THE CLOUD

Buying Intel Data Center GPU Max 1350 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
8747
TOK/S · 1% VRAM
S
SmolLM2 135M0.135B
SMOLLM·2K CTX· CHAT
5831
TOK/S · 1% VRAM
S
nomic-embed-text-v1.5 100M0.14B
EMBEDDING·8K CTX· CHAT
5623
TOK/S · 1% VRAM
S
GPT-2 124M0.14B
GPT2·1K CTX· CHAT
5623
TOK/S · 1% VRAM
S
SmolVLM 256M0.256B
SMOLLM·8K CTX· CHAT· VISION
3075
TOK/S · 1% VRAM
S
Gemma 3 270M0.27B
GEMMA·32K CTX· CHAT
2916
TOK/S · 1% VRAM
S
Snowflake Arctic Embed M v2.00.305B
EMBEDDING·8K CTX· EMBEDDING· MULTILINGUAL
2581
TOK/S · 1% VRAM
S
bge-large-en-v1.5 335M0.335B
EMBEDDING·1K CTX· CHAT
2350
TOK/S · 1% VRAM
S
mxbai-embed-large-v10.335B
EMBEDDING·1K CTX· EMBEDDING
2350
TOK/S · 1% VRAM
S
Snowflake Arctic Embed L0.335B
EMBEDDING·1K CTX· EMBEDDING
2350
TOK/S · 1% VRAM
S
LFM2 350M0.35B
LFM·125K CTX· CHAT· TOOL_USE
2249
TOK/S · 1% VRAM
S
SmolLM2 360M0.36B
SMOLLM·8K CTX· CHAT
2187
TOK/S · 1% VRAM
S
GPT-2 Medium 345M0.38B
GPT2·1K CTX· CHAT
2072
TOK/S · 1% VRAM
S
Qwen 2.5 0.5B0.5B
QWEN·32K CTX· CHAT
1574
TOK/S · 1% VRAM
S
SmolVLM 500M0.5B
SMOLLM·8K CTX· CHAT· VISION
1574
TOK/S · 1% VRAM
S
Falcon-H1 0.5B0.52B
FALCON·128K CTX· CHAT
1514
TOK/S · 1% VRAM
S
BGE-M30.568B
EMBEDDING·8K CTX· EMBEDDING
1386
TOK/S · 1% VRAM
S
Snowflake Arctic Embed L v2.00.568B
EMBEDDING·8K CTX· EMBEDDING· MULTILINGUAL
1386
TOK/S · 1% VRAM
S
Qwen3-Embedding 0.6B0.6B
EMBEDDING·32K CTX· EMBEDDING· MULTILINGUAL
1312
TOK/S · 1% VRAM
S
Falcon-H1R Tiny 0.6B0.6B
FALCON·32K CTX· CHAT· REASONING
1312
TOK/S · 1% VRAM
S
Falcon Perception 0.6B0.6B
FALCON·4K CTX· VISION
1312
TOK/S · 1% VRAM
S
Qwen 1.5 0.5B0.62B
QWEN·32K CTX· CHAT
1270
TOK/S · 1% VRAM
S
LFM2 700M0.74B
LFM·125K CTX· CHAT· TOOL_USE
1064
TOK/S · 1% VRAM
S
Qwen3 0.6B0.75B
QWEN·32K CTX· CHAT· REASONING
1050
TOK/S · 1% VRAM
S
GPT-2 Large 774M0.81B
GPT2·1K CTX· CHAT
972
TOK/S · 1% VRAM
S
Qwen 3.5 0.8B0.87B
QWEN·256K CTX· CHAT· CODING· MULTILINGUAL
905
TOK/S · 1% VRAM
S
InternVL3 1B0.94B
OTHER·32K CTX· CHAT· VISION
837
TOK/S · 1% VRAM
S
MiniCPM5 1B1.08B
MINICPM·128K CTX· CHAT· REASONING· MULTILINGUAL
729
TOK/S · 1% VRAM
S
TinyLlama 1.1B1.1B
LLAMA·2K CTX· CHAT
716
TOK/S · 1% VRAM
S
LFM2.5-1.2B-Thinking1.2B
LFM·122K CTX· CHAT· REASONING· TOOL_USE
656
TOK/S · 1% VRAM
S
Llama-3.2-1B1.2B
LLAMA·4K CTX· CHAT
656
TOK/S · 1% VRAM
S
LFM2 1.2B1.2B
LFM·125K CTX· CHAT· TOOL_USE· MULTILINGUAL
656
TOK/S · 1% VRAM
S
Zamba2 1.2B1.2B
OTHER·4K CTX· CHAT
656
TOK/S · 1% VRAM
S
EXAONE-4.0-1.2B1.3B
EXAONE·64K CTX· CHAT
606
TOK/S · 1% VRAM
S
OPT 1.3B1.3B
OPT·2K CTX· CHAT
606
TOK/S · 1% VRAM
S
MiniCPM-V 4.61.3B
OTHER·256K CTX· CHAT· VISION
606
TOK/S · 1% VRAM
S
DeepSeek Coder 1.3B1.35B
DEEPSEEK·16K CTX· CODING
583
TOK/S · 1% VRAM
S
Phi-1 1.3B1.42B
PHI·2K CTX· CODING
554
TOK/S · 1% VRAM
S
Phi-1.5 1.3B1.42B
PHI·2K CTX· CHAT· CODING
554
TOK/S · 1% VRAM
S
LFM2 8B A1B8.3BMoE
LFM·125K CTX· CHAT· TOOL_USE· MULTILINGUAL
525
TOK/S · 6% VRAM
▸ NEXT STEP

Get personalized recommendations.

See ranked models with benchmark scores, run commands, and precise speed estimates for your Data Center GPU Max 1350.

WHAT THIS CARD IS WORTH

Data Center GPU Max 1350 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
8B at Q4_K_M, so cards compare like for like
VRAM PER $100
what memory costs on this card
THE BIGGEST IT TAKES
dots.llm1.inst 142.8B142.8B · IQ4_XS86.0 GB6 tok/sEST
WizardLM 2 8x22B141B · Q4_K_S85.7 GB19 tok/sEST
Mixtral-8x22B140.6B · Q4_K_S85.5 GB19 tok/sEST
DBRX 132B132B · Q4_K_M83.8 GB20 tok/sEST
Mistral Medium 3.5128B · Q4_K_M82.1 GB6 tok/sEST
Pixtral Large 124B124B · Q4_K_M79.7 GB6 tok/sEST
Nemotron 3 Super 120B-A12B123.61B · Q4_K_M78.4 GB60 tok/sEST
Mistral-Large 123B123B · Q4_K_M79.1 GB6 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
Data Center GPU Max 135096 GB

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

Intel Data Center GPU Max 1350 — 96 GB VRAM.

DATA CENTER GPU MAX 1350 SPEC
BRAND
Intel
VRAM
96 GB HBM2e
BANDWIDTH
2460 GB/s
FP16 COMPUTE
44.4 TFLOPS
FP32 COMPUTE
44.4 TFLOPS
TDP
450 W
ARCHITECTURE
Generation 12.5
▸ AI CAPABILITY
392/ 449 models @ Q4

With 96 GB VRAM and 2460 GB/s bandwidth, this GPU handles models up to 132B parameters.

Speed ≈ bandwidth / model_size × efficiency. A 7B model at Q4 runs at ~281 tok/s.

RENT IT — LIVE PRICES
Checking what the clouds are charging…
§ 01TOP MODELS FOR DATA CENTER GPU MAX 1350
392 FIT · SHOWING 20
MODELSIZEVRAM Q4TOK/SAVG
DBRX 132B132B81.2 GB2246.3
Mistral Medium 3.5128B78.7 GB646.6
Pixtral Large 124B124B76.3 GB639.3
Nemotron 3 Super 120B-A12B123.61B76.0 GB6653.2
Mistral-Large 123B123B75.7 GB633.5
Devstral 2 123B123B75.7 GB638.1
Qwen 3.5 122B A10B122B75.1 GB7956.8
Nemotron 3 Super 120B120B73.8 GB6657.3
Mistral Small 4 119B119B73.2 GB12150.2
GPT-OSS 120B117B72.0 GB15454.1
Command A 111B111B68.3 GB727.6
GLM 4.5 Air110B67.7 GB6651.0
Qwen 1.5 110B110B67.7 GB733.4
Llama 4 Scout 17B-16E109B67.1 GB4633.9
Cogito v2 109B MoE109B67.1 GB46
Ling 2.6 Flash107.49B66.2 GB10636.8
Sarvam 105B105B64.7 GB748.0
Command-R+ 104B104B64.1 GB852.7
Llama-3.2-90B-Vision-Instruct90B55.5 GB948.5
Hunyuan A13B80B49.4 GB6181.1