FitMyLLM
▸ AMD· CDNA2

AMD Instinct MI250X

Running LLMs on the Instinct MI250X — the long read: which models fit at which quantisation, and the settings worth changing. · Or what else $10,000 buys

VRAM
128 GB
FLAGSHIP
BANDWIDTH
3277
GB/S
MODELS Q4
397/449
88%
7B Q4 SPEED
~416
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
~971
TOK/S
7B
~416
TOK/S
14B
~208
TOK/S
32B
~91
TOK/S
70B
~42
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
128 GB
BANDWIDTH
3277 GB/s
FP16 COMPUTE
383 TFLOPS
TDP
560W
MEMORY
HBM2e
ARCHITECTURE
CDNA2
PCIE
Gen 4 x16
MSRP
$10,000
386
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 Instinct MI250X 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
32365
TOK/S · 0% VRAM
›
S
SmolLM2 135M0.135B
SMOLLM·2K CTX· CHAT
21577
TOK/S · 0% VRAM
›
S
nomic-embed-text-v1.5 100M0.14B
EMBEDDING·8K CTX· CHAT
20806
TOK/S · 0% VRAM
›
S
GPT-2 124M0.14B
GPT2·1K CTX· CHAT
20806
TOK/S · 0% VRAM
›
S
SmolVLM 256M0.256B
SMOLLM·8K CTX· CHAT· VISION
11378
TOK/S · 1% VRAM
›
S
Gemma 3 270M0.27B
GEMMA·32K CTX· CHAT
10788
TOK/S · 1% VRAM
›
S
Snowflake Arctic Embed M v2.00.305B
EMBEDDING·8K CTX· EMBEDDING· MULTILINGUAL
9550
TOK/S · 1% VRAM
›
S
bge-large-en-v1.5 335M0.335B
EMBEDDING·1K CTX· CHAT
8695
TOK/S · 1% VRAM
›
S
mxbai-embed-large-v10.335B
EMBEDDING·1K CTX· EMBEDDING
8695
TOK/S · 1% VRAM
›
S
Snowflake Arctic Embed L0.335B
EMBEDDING·1K CTX· EMBEDDING
8695
TOK/S · 1% VRAM
›
S
LFM2 350M0.35B
LFM·125K CTX· CHAT· TOOL_USE
8323
TOK/S · 1% VRAM
›
S
SmolLM2 360M0.36B
SMOLLM·8K CTX· CHAT
8091
TOK/S · 1% VRAM
›
S
GPT-2 Medium 345M0.38B
GPT2·1K CTX· CHAT
7665
TOK/S · 1% VRAM
›
S
Qwen 2.5 0.5B0.5B
QWEN·32K CTX· CHAT
5826
TOK/S · 1% VRAM
›
S
SmolVLM 500M0.5B
SMOLLM·8K CTX· CHAT· VISION
5826
TOK/S · 1% VRAM
›
S
Falcon-H1 0.5B0.52B
FALCON·128K CTX· CHAT
5602
TOK/S · 1% VRAM
›
S
BGE-M30.568B
EMBEDDING·8K CTX· EMBEDDING
5128
TOK/S · 1% VRAM
›
S
Snowflake Arctic Embed L v2.00.568B
EMBEDDING·8K CTX· EMBEDDING· MULTILINGUAL
5128
TOK/S · 1% VRAM
›
S
Qwen3-Embedding 0.6B0.6B
EMBEDDING·32K CTX· EMBEDDING· MULTILINGUAL
4855
TOK/S · 1% VRAM
›
S
Falcon-H1R Tiny 0.6B0.6B
FALCON·32K CTX· CHAT· REASONING
4855
TOK/S · 1% VRAM
›
S
Falcon Perception 0.6B0.6B
FALCON·4K CTX· VISION
4855
TOK/S · 1% VRAM
›
S
Qwen 1.5 0.5B0.62B
QWEN·32K CTX· CHAT
4698
TOK/S · 1% VRAM
›
S
LFM2 700M0.74B
LFM·125K CTX· CHAT· TOOL_USE
3936
TOK/S · 1% VRAM
›
S
Qwen3 0.6B0.75B
QWEN·32K CTX· CHAT· REASONING
3884
TOK/S · 1% VRAM
›
S
GPT-2 Large 774M0.81B
GPT2·1K CTX· CHAT
3596
TOK/S · 1% VRAM
›
S
Qwen 3.5 0.8B0.87B
QWEN·256K CTX· CHAT· CODING· MULTILINGUAL
3348
TOK/S · 1% VRAM
›
S
InternVL3 1B0.94B
OTHER·32K CTX· CHAT· VISION
3099
TOK/S · 1% VRAM
›
S
MiniCPM5 1B1.08B
MINICPM·128K CTX· CHAT· REASONING· MULTILINGUAL
2697
TOK/S · 1% VRAM
›
S
TinyLlama 1.1B1.1B
LLAMA·2K CTX· CHAT
2648
TOK/S · 1% VRAM
›
S
LFM2.5-1.2B-Thinking1.2B
LFM·122K CTX· CHAT· REASONING· TOOL_USE
2427
TOK/S · 1% VRAM
›
S
Llama-3.2-1B1.2B
LLAMA·4K CTX· CHAT
2427
TOK/S · 1% VRAM
›
S
LFM2 1.2B1.2B
LFM·125K CTX· CHAT· TOOL_USE· MULTILINGUAL
2427
TOK/S · 1% VRAM
›
S
Zamba2 1.2B1.2B
OTHER·4K CTX· CHAT
2427
TOK/S · 1% VRAM
›
S
EXAONE-4.0-1.2B1.3B
EXAONE·64K CTX· CHAT
2241
TOK/S · 1% VRAM
›
S
OPT 1.3B1.3B
OPT·2K CTX· CHAT
2241
TOK/S · 1% VRAM
›
S
MiniCPM-V 4.61.3B
OTHER·256K CTX· CHAT· VISION
2241
TOK/S · 1% VRAM
›
S
DeepSeek Coder 1.3B1.35B
DEEPSEEK·16K CTX· CODING
2158
TOK/S · 1% VRAM
›
S
Phi-1 1.3B1.42B
PHI·2K CTX· CODING
2051
TOK/S · 1% VRAM
›
S
Phi-1.5 1.3B1.42B
PHI·2K CTX· CHAT· CODING
2051
TOK/S · 1% VRAM
›
S
LFM2 8B A1B8.3BMoE
LFM·125K CTX· CHAT· TOOL_USE· MULTILINGUAL
1942
TOK/S · 4% VRAM
›
▸ NEXT STEP

Get personalized recommendations.

See ranked models with benchmark scores, run commands, and precise speed estimates for your Instinct MI250X.

WHAT THIS CARD IS WORTH

Instinct MI250X holds 397 of the models in our catalogue and is, in practice, a IQ4_XS card — the largest it takes is Step 3.7 Flash at IQ4_XS.

TOKENS/SEC PER $100
3.5
8B at Q4_K_M, so cards compare like for like
VRAM PER $100
1.28 GB
what memory costs on this card
THE BIGGEST IT TAKES
Step 3.7 Flash201.37B · IQ4_XS115.0 GB274 tok/sEST
Falcon 180B180B · Q4_K_M113.8 GB19 tok/sEST
dots.llm1.inst 142.8B142.8B · Q5_K_M108.1 GB21 tok/sEST
WizardLM 2 8x22B141B · Q5_K_M103.8 GB76 tok/sEST
Mixtral-8x22B140.6B · Q5_K_M103.6 GB76 tok/sEST
DBRX 132B132B · Q6_K111.4 GB72 tok/sEST
Mistral Medium 3.5128B · Q6_K108.8 GB20 tok/sEST
Pixtral Large 124B124B · Q6_K105.6 GB21 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
Instinct MI250X128 GB$10,0003.5 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

AMD Instinct MI250X — 128 GB VRAM.

▸ INSTINCT MI250X SPEC
BRAND
AMD
VRAM
128 GB HBM2e
BANDWIDTH
3277 GB/s
FP16 COMPUTE
383 TFLOPS
FP32 COMPUTE
47.9 TFLOPS
TDP
560 W
ARCHITECTURE
CDNA2
MSRP
$10000
▸ AI CAPABILITY
397/ 449 models @ Q4

With 128 GB VRAM and 3277 GB/s bandwidth, this GPU handles models up to 180B parameters.

Speed ≈ bandwidth / model_size × efficiency. A 7B model at Q4 runs at ~375 tok/s.

RENT IT — LIVE PRICES
Checking what the clouds are charging…
§ 01TOP MODELS FOR INSTINCT MI250X
397 FIT · SHOWING 20
MODELSIZEVRAM Q4TOK/SAVG
Falcon 180B180B110.5 GB1651.3
bloom 176.2B176.2B108.2 GB1715.0
dots.llm1.inst 142.8B142.8B87.8 GB20—
WizardLM 2 8x22B141B86.7 GB7542.4
Mixtral-8x22B140.6B86.4 GB7431.9
DBRX 132B132B81.2 GB8146.3
Mistral Medium 3.5128B78.7 GB2346.6
Pixtral Large 124B124B76.3 GB2339.3
Nemotron 3 Super 120B-A12B123.61B76.0 GB24353.2
Mistral-Large 123B123B75.7 GB2433.5
Devstral 2 123B123B75.7 GB2438.1
Qwen 3.5 122B A10B122B75.1 GB29156.8
Nemotron 3 Super 120B120B73.8 GB24357.3
Mistral Small 4 119B119B73.2 GB44850.2
GPT-OSS 120B117B72.0 GB57154.1
Command A 111B111B68.3 GB2627.6
GLM 4.5 Air110B67.7 GB24351.0
Qwen 1.5 110B110B67.7 GB2633.4
Llama 4 Scout 17B-16E109B67.1 GB17133.9
Cogito v2 109B MoE109B67.1 GB171—