FitMyLLM
AMD· CDNA 3.0

AMD Radeon Instinct MI300X

Running LLMs on the Radeon Instinct MI300X — the long read: which models fit at which quantisation, and the settings worth changing. · Or what else $15,000 buys

VRAM
192 GB
FLAGSHIP
BANDWIDTH
10300
GB/S
MODELS Q4
407/449
91%
7B Q4 SPEED
~1308
BLAZING
▸ MODEL COVERAGE @ Q491% OF ALL
▸ ESTIMATED SPEED· BY MODEL SIZE @ Q4

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

3B
~3052
TOK/S
7B
~1308
TOK/S
14B
~654
TOK/S
32B
~286
TOK/S
70B
~131
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
192 GB
BANDWIDTH
10300 GB/s
FP16 COMPUTE
653.7 TFLOPS
TDP
750W
MEMORY
HBM3
ARCHITECTURE
CDNA 3.0
STREAM PROCESSORS
19,456
COMPUTE UNITS
152
PCIE
Gen 5 x16
MSRP
$15,000
407
FAST MODELS · >30 TOK/S
Real-time chat speed
407
USABLE · >10 TOK/S
Comfortable for all tasks
407
TOTAL COMPATIBLE
Fit in VRAM at Q4
▸ RENT IT IN THE CLOUD

Buying Radeon Instinct MI300X 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· 407
S
Falcon-H1R Tiny 90M0.09B
FALCON·256K CTX· CHAT· REASONING
101728
TOK/S · 0% VRAM
S
SmolLM2 135M0.135B
SMOLLM·2K CTX· CHAT
67819
TOK/S · 0% VRAM
S
nomic-embed-text-v1.5 100M0.14B
EMBEDDING·8K CTX· CHAT
65397
TOK/S · 0% VRAM
S
GPT-2 124M0.14B
GPT2·1K CTX· CHAT
65397
TOK/S · 0% VRAM
S
SmolVLM 256M0.256B
SMOLLM·8K CTX· CHAT· VISION
35764
TOK/S · 0% VRAM
S
Gemma 3 270M0.27B
GEMMA·32K CTX· CHAT
33909
TOK/S · 0% VRAM
S
Snowflake Arctic Embed M v2.00.305B
EMBEDDING·8K CTX· EMBEDDING· MULTILINGUAL
30018
TOK/S · 0% VRAM
S
bge-large-en-v1.5 335M0.335B
EMBEDDING·1K CTX· CHAT
27330
TOK/S · 0% VRAM
S
mxbai-embed-large-v10.335B
EMBEDDING·1K CTX· EMBEDDING
27330
TOK/S · 0% VRAM
S
Snowflake Arctic Embed L0.335B
EMBEDDING·1K CTX· EMBEDDING
27330
TOK/S · 0% VRAM
S
LFM2 350M0.35B
LFM·125K CTX· CHAT· TOOL_USE
26159
TOK/S · 0% VRAM
S
SmolLM2 360M0.36B
SMOLLM·8K CTX· CHAT
25432
TOK/S · 0% VRAM
S
GPT-2 Medium 345M0.38B
GPT2·1K CTX· CHAT
24094
TOK/S · 0% VRAM
S
Qwen 2.5 0.5B0.5B
QWEN·32K CTX· CHAT
18311
TOK/S · 0% VRAM
S
SmolVLM 500M0.5B
SMOLLM·8K CTX· CHAT· VISION
18311
TOK/S · 0% VRAM
S
Falcon-H1 0.5B0.52B
FALCON·128K CTX· CHAT
17607
TOK/S · 0% VRAM
S
BGE-M30.568B
EMBEDDING·8K CTX· EMBEDDING
16119
TOK/S · 0% VRAM
S
Snowflake Arctic Embed L v2.00.568B
EMBEDDING·8K CTX· EMBEDDING· MULTILINGUAL
16119
TOK/S · 0% VRAM
S
Qwen3-Embedding 0.6B0.6B
EMBEDDING·32K CTX· EMBEDDING· MULTILINGUAL
15259
TOK/S · 0% VRAM
S
Falcon-H1R Tiny 0.6B0.6B
FALCON·32K CTX· CHAT· REASONING
15259
TOK/S · 0% VRAM
S
Falcon Perception 0.6B0.6B
FALCON·4K CTX· VISION
15259
TOK/S · 0% VRAM
S
Qwen 1.5 0.5B0.62B
QWEN·32K CTX· CHAT
14767
TOK/S · 0% VRAM
S
LFM2 700M0.74B
LFM·125K CTX· CHAT· TOOL_USE
12372
TOK/S · 0% VRAM
S
Qwen3 0.6B0.75B
QWEN·32K CTX· CHAT· REASONING
12207
TOK/S · 0% VRAM
S
GPT-2 Large 774M0.81B
GPT2·1K CTX· CHAT
11303
TOK/S · 1% VRAM
S
Qwen 3.5 0.8B0.87B
QWEN·256K CTX· CHAT· CODING· MULTILINGUAL
10524
TOK/S · 1% VRAM
S
InternVL3 1B0.94B
OTHER·32K CTX· CHAT· VISION
9740
TOK/S · 1% VRAM
S
MiniCPM5 1B1.08B
MINICPM·128K CTX· CHAT· REASONING· MULTILINGUAL
8477
TOK/S · 1% VRAM
S
TinyLlama 1.1B1.1B
LLAMA·2K CTX· CHAT
8323
TOK/S · 1% VRAM
S
LFM2.5-1.2B-Thinking1.2B
LFM·122K CTX· CHAT· REASONING· TOOL_USE
7630
TOK/S · 1% VRAM
S
Llama-3.2-1B1.2B
LLAMA·4K CTX· CHAT
7630
TOK/S · 1% VRAM
S
LFM2 1.2B1.2B
LFM·125K CTX· CHAT· TOOL_USE· MULTILINGUAL
7630
TOK/S · 1% VRAM
S
Zamba2 1.2B1.2B
OTHER·4K CTX· CHAT
7630
TOK/S · 1% VRAM
S
EXAONE-4.0-1.2B1.3B
EXAONE·64K CTX· CHAT
7043
TOK/S · 1% VRAM
S
OPT 1.3B1.3B
OPT·2K CTX· CHAT
7043
TOK/S · 1% VRAM
S
MiniCPM-V 4.61.3B
OTHER·256K CTX· CHAT· VISION
7043
TOK/S · 1% VRAM
S
DeepSeek Coder 1.3B1.35B
DEEPSEEK·16K CTX· CODING
6782
TOK/S · 1% VRAM
S
Phi-1 1.3B1.42B
PHI·2K CTX· CODING
6448
TOK/S · 1% VRAM
S
Phi-1.5 1.3B1.42B
PHI·2K CTX· CHAT· CODING
6448
TOK/S · 1% VRAM
S
LFM2 8B A1B8.3BMoE
LFM·125K CTX· CHAT· TOOL_USE· MULTILINGUAL
6104
TOK/S · 3% VRAM
▸ NEXT STEP

Get personalized recommendations.

See ranked models with benchmark scores, run commands, and precise speed estimates for your Radeon Instinct MI300X.

WHAT THIS CARD IS WORTH

Radeon Instinct MI300X holds 407 of the models in our catalogue and is, in practice, a IQ4_XS card — the largest it takes is DeepSeek V4 Flash 0731 at IQ4_XS.

TOKENS/SEC PER $100
7.3
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
DeepSeek V4 Flash 0731304.18B · IQ4_XS172.4 GB754 tok/sEST
ERNIE-4.5-300B-A47B-Paddle300.5B · IQ4_XS170.9 GB40 tok/sEST
ERNIE 4.5 300B-A47B300B · IQ4_XS170.6 GB255 tok/sEST
Hunyuan Hy3-preview295B · IQ4_XS168.2 GB511 tok/sEST
DeepSeek V4 Flash290.94B · Q4_K_S172.7 GB726 tok/sEST
DeepSeek V2 236B236B · Q5_K_M170.9 GB418 tok/sEST
DeepSeek-V2.5 236B236B · Q5_K_M170.9 GB418 tok/sEST
DeepSeek-Coder-V2 236B236B · Q5_K_M170.9 GB418 tok/sEST
AGAINST CARDS OF SIMILAR MEMORY
Radeon Instinct MI300A192 GB$12,0009.2 tok/s per $100
Radeon Instinct MI308X192 GB$12,0009.2 tok/s per $100
Instinct MI300X192 GB$15,0003.8 tok/s per $100
M4 Ultra (192GB)144 GB$7,4991.2 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 Radeon Instinct MI300X — 192 GB VRAM.

RADEON INSTINCT MI300X SPEC
BRAND
AMD
VRAM
192 GB HBM3
BANDWIDTH
10300 GB/s
FP16 COMPUTE
653.7 TFLOPS
FP32 COMPUTE
81.7 TFLOPS
STREAM PROCESSORS
19,456
TDP
750 W
ARCHITECTURE
CDNA 3.0
MSRP
$15000
▸ AI CAPABILITY
407/ 449 models @ Q4

With 192 GB VRAM and 10300 GB/s bandwidth, this GPU handles models up to 236B parameters.

Speed ≈ bandwidth / model_size × efficiency. A 7B model at Q4 runs at ~1177 tok/s.

RENT IT — LIVE PRICES
Checking what the clouds are charging…
§ 01TOP MODELS FOR RADEON INSTINCT MI300X
407 FIT · SHOWING 20
MODELSIZEVRAM Q4TOK/SAVG
DeepSeek V2 236B236B144.7 GB43640.4
DeepSeek-V2.5 236B236B144.7 GB43664.0
DeepSeek-Coder-V2 236B236B144.7 GB43661.8
Qwen3-235B-A22B235.1B144.2 GB41655.9
Qwen3-235B-A22B Instruct 2507235.1B144.2 GB41651.9
Qwen3-VL 235B A22B Instruct235B144.1 GB41644.3
MiniMax-M2.7230B141.1 GB91658.1
MiniMax-M2.5 228.7B228.7B140.3 GB43662.6
Command A+218B133.7 GB36641.8
Step 3.7 Flash201.37B123.6 GB83253.8
Falcon 180B180B110.5 GB5151.3
bloom 176.2B176.2B108.2 GB5215.0
dots.llm1.inst 142.8B142.8B87.8 GB64
WizardLM 2 8x22B141B86.7 GB23542.4
Mixtral-8x22B140.6B86.4 GB23431.9
DBRX 132B132B81.2 GB25446.3
Mistral Medium 3.5128B78.7 GB7246.6
Pixtral Large 124B124B76.3 GB7439.3
Nemotron 3 Super 120B-A12B123.61B76.0 GB76353.2
Mistral-Large 123B123B75.7 GB7433.5