FitMyLLM
INTEL· XE-HPG

Intel Data Center GPU Flex 140

Running LLMs on the Data Center GPU Flex 140 — the long read: which models fit at which quantisation, and the settings worth changing. · Or what a budget buys

VRAM
6 GB
BUDGET
BANDWIDTH
186
GB/S
MODELS Q4
130/449
29%
7B Q4 SPEED
~9
USABLE
▸ MODEL COVERAGE @ Q429% OF ALL
▸ ESTIMATED SPEED· BY MODEL SIZE @ Q4

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

3B
~20
TOK/S
7B
~9
TOK/S
14B
7.9GB NEEDED
32B
18.0GB NEEDED
70B
39.4GB NEEDED
▸ 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
6 GB
BANDWIDTH
186 GB/s
FP16 COMPUTE
8 TFLOPS
TDP
75W
MEMORY
GDDR6
ARCHITECTURE
Xe-HPG
COMPUTE UNITS
64
PCIE
Gen 4 x8
55
FAST MODELS · >30 TOK/S
Real-time chat speed
113
USABLE · >10 TOK/S
Comfortable for all tasks
130
TOTAL COMPATIBLE
Fit in VRAM at Q4
▸ DON’T WANT TO BUY?

Test Data Center GPU Flex 140 (or anything bigger) without committing. Pay by the second, cancel anytime.

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

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▸ COMPATIBLE MODELS· 130
S
Falcon-H1R Tiny 90M0.09B
FALCON·256K CTX· CHAT· REASONING
661
TOK/S · 9% VRAM
S
SmolLM2 135M0.135B
SMOLLM·2K CTX· CHAT
441
TOK/S · 10% VRAM
S
nomic-embed-text-v1.5 100M0.14B
EMBEDDING·8K CTX· CHAT
425
TOK/S · 10% VRAM
S
GPT-2 124M0.14B
GPT2·1K CTX· CHAT
425
TOK/S · 10% VRAM
S
SmolVLM 256M0.256B
SMOLLM·8K CTX· CHAT· VISION
232
TOK/S · 11% VRAM
S
Gemma 3 270M0.27B
GEMMA·32K CTX· CHAT
220
TOK/S · 11% VRAM
S
Snowflake Arctic Embed M v2.00.305B
EMBEDDING·8K CTX· EMBEDDING· MULTILINGUAL
195
TOK/S · 11% VRAM
S
bge-large-en-v1.5 335M0.335B
EMBEDDING·1K CTX· CHAT
178
TOK/S · 12% VRAM
S
mxbai-embed-large-v10.335B
EMBEDDING·1K CTX· EMBEDDING
178
TOK/S · 12% VRAM
S
Snowflake Arctic Embed L0.335B
EMBEDDING·1K CTX· EMBEDDING
178
TOK/S · 12% VRAM
S
LFM2 350M0.35B
LFM·125K CTX· CHAT· TOOL_USE
170
TOK/S · 12% VRAM
S
SmolLM2 360M0.36B
SMOLLM·8K CTX· CHAT
165
TOK/S · 12% VRAM
S
GPT-2 Medium 345M0.38B
GPT2·1K CTX· CHAT
157
TOK/S · 12% VRAM
S
Qwen 2.5 0.5B0.5B
QWEN·32K CTX· CHAT
119
TOK/S · 13% VRAM
S
SmolVLM 500M0.5B
SMOLLM·8K CTX· CHAT· VISION
119
TOK/S · 13% VRAM
S
Falcon-H1 0.5B0.52B
FALCON·128K CTX· CHAT
114
TOK/S · 13% VRAM
S
BGE-M30.568B
EMBEDDING·8K CTX· EMBEDDING
105
TOK/S · 14% VRAM
S
Snowflake Arctic Embed L v2.00.568B
EMBEDDING·8K CTX· EMBEDDING· MULTILINGUAL
105
TOK/S · 14% VRAM
S
Qwen3-Embedding 0.6B0.6B
EMBEDDING·32K CTX· EMBEDDING· MULTILINGUAL
99
TOK/S · 14% VRAM
S
Falcon-H1R Tiny 0.6B0.6B
FALCON·32K CTX· CHAT· REASONING
99
TOK/S · 14% VRAM
S
Falcon Perception 0.6B0.6B
FALCON·4K CTX· VISION
99
TOK/S · 14% VRAM
S
Qwen 1.5 0.5B0.62B
QWEN·32K CTX· CHAT
96
TOK/S · 14% VRAM
S
LFM2 700M0.74B
LFM·125K CTX· CHAT· TOOL_USE
80
TOK/S · 16% VRAM
S
Qwen3 0.6B0.75B
QWEN·32K CTX· CHAT· REASONING
79
TOK/S · 16% VRAM
S
GPT-2 Large 774M0.81B
GPT2·1K CTX· CHAT
73
TOK/S · 16% VRAM
S
Qwen 3.5 0.8B0.87B
QWEN·256K CTX· CHAT· CODING· MULTILINGUAL
68
TOK/S · 17% VRAM
S
InternVL3 1B0.94B
OTHER·32K CTX· CHAT· VISION
63
TOK/S · 18% VRAM
A
MiniCPM5 1B1.08B
MINICPM·128K CTX· CHAT· REASONING· MULTILINGUAL
55
TOK/S · 19% VRAM
A
TinyLlama 1.1B1.1B
LLAMA·2K CTX· CHAT
54
TOK/S · 19% VRAM
A
LFM2.5-1.2B-Thinking1.2B
LFM·122K CTX· CHAT· REASONING· TOOL_USE
50
TOK/S · 20% VRAM
A
Llama-3.2-1B1.2B
LLAMA·4K CTX· CHAT
50
TOK/S · 20% VRAM
A
LFM2 1.2B1.2B
LFM·125K CTX· CHAT· TOOL_USE· MULTILINGUAL
50
TOK/S · 20% VRAM
A
Zamba2 1.2B1.2B
OTHER·4K CTX· CHAT
50
TOK/S · 20% VRAM
A
EXAONE-4.0-1.2B1.3B
EXAONE·64K CTX· CHAT
46
TOK/S · 21% VRAM
A
OPT 1.3B1.3B
OPT·2K CTX· CHAT
46
TOK/S · 21% VRAM
A
MiniCPM-V 4.61.3B
OTHER·256K CTX· CHAT· VISION
46
TOK/S · 21% VRAM
A
DeepSeek Coder 1.3B1.35B
DEEPSEEK·16K CTX· CODING
44
TOK/S · 22% VRAM
A
Phi-1 1.3B1.42B
PHI·2K CTX· CODING
42
TOK/S · 23% VRAM
A
Phi-1.5 1.3B1.42B
PHI·2K CTX· CHAT· CODING
42
TOK/S · 23% VRAM
A
granite-4.0-h-tiny 6.9B6.9BMoE
GRANITE·128K CTX· CHAT
40
TOK/S · 78% VRAM
▸ NEXT STEP

Get personalized recommendations.

See ranked models with benchmark scores, run commands, and precise speed estimates for your Data Center GPU Flex 140.

WHAT THIS CARD IS WORTH

Data Center GPU Flex 140 holds 130 of the models in our catalogue and is, in practice, a Q4_K_M card — the largest it takes is Falcon-H1 7B at Q4_K_M.

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
Falcon-H1 7B7.59B · Q4_K_M5.4 GB7 tok/sEST
Falcon-H1R 7B7.59B · Q4_K_M5.4 GB7 tok/sEST
Falcon Mamba 7B7.27B · Q4_K_M5.0 GB8 tok/sEST
WizardLM 2 7B7B · Q4_K_M5.3 GB8 tok/sEST
StarCoder2 7B7B · Q4_K_M5.0 GB8 tok/sEST
Dolly v2 7B6.9B · Q4_K_M5.3 GB8 tok/sEST
granite-4.0-h-tiny 6.9B6.9B · Q4_K_M5.0 GB37 tok/sEST
ChatGLM2 6B6.24B · Q5_K_M5.1 GB8 tok/sEST
AGAINST CARDS OF SIMILAR MEMORY
RTX 3080 10GB10 GB$42917.7 tok/s per $100
Arc B57010 GB$2198.2 tok/s per $100
Radeon RX 670010 GB$29912.0 tok/s per $100
Radeon RX 6750 GRE 10 GB10 GB$22915.7 tok/s per $100
Data Center GPU Flex 1406 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 Flex 140 — 6 GB VRAM.

DATA CENTER GPU FLEX 140 SPEC
BRAND
Intel
VRAM
6 GB GDDR6
BANDWIDTH
186 GB/s
FP16 COMPUTE
8 TFLOPS
FP32 COMPUTE
4 TFLOPS
TDP
75 W
ARCHITECTURE
Xe-HPG
▸ AI CAPABILITY
130/ 449 models @ Q4

With 6 GB VRAM and 186 GB/s bandwidth, this GPU handles models up to 7B parameters.

Speed ≈ bandwidth / model_size × efficiency. A 7B model at Q4 runs at ~21 tok/s.

RENT IT — LIVE PRICES
Checking what the clouds are charging…
§ 01TOP MODELS FOR DATA CENTER GPU FLEX 140
130 FIT · SHOWING 20
MODELSIZEVRAM Q4TOK/SAVG
Alpaca 7B7B4.8 GB927.7
Baichuan2 7B7B4.8 GB921.5
Vicuna 7B7B4.8 GB922.0
MPT-7B7B4.8 GB97.8
Orca 2 7B7B4.8 GB926.1
WizardLM 2 7B7B4.8 GB926.1
StarCoder2 7B7B4.8 GB917.0
WizardCoder Python 7B7B4.8 GB953.7
WizardLM 7B7B4.8 GB915.5
OLMo 3.1 RLZero 7B Code7B4.8 GB921.8
OLMo 3.1 RLZero 7B Math7B4.8 GB921.8
Dolly v2 7B6.9B4.7 GB97.0
granite-4.0-h-tiny 6.9B6.9B4.7 GB4049.2
Llama 2 7B6.74B4.6 GB921.1
CodeLlama 7B6.74B4.6 GB928.1
LLaMA 1 7B6.74B4.6 GB930.8
DeepSeek Coder 6.7B6.7B4.6 GB923.6
OPT 6.7B6.7B4.6 GB918.5
ChatGLM2 6B6.24B4.3 GB1020.7
ChatGLM3 6B6.24B4.3 GB1042.7