FitMyLLM
AMD· GCN 5.1

AMD Radeon Pro Vega II

Running LLMs on the Radeon Pro Vega II — the long read: which models fit at which quantisation, and the settings worth changing. · Or what a budget buys

VRAM
32 GB
HIGH-END
BANDWIDTH
825
GB/S
MODELS Q4
337/449
75%
7B Q4 SPEED
~105
BLAZING
▸ MODEL COVERAGE @ Q475% OF ALL
▸ ESTIMATED SPEED· BY MODEL SIZE @ Q4

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

3B
~244
TOK/S
7B
~105
TOK/S
14B
~52
TOK/S
32B
~23
TOK/S
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
32 GB
BANDWIDTH
825 GB/s
FP16 COMPUTE
28.2 TFLOPS
TDP
475W
MEMORY
HBM2
ARCHITECTURE
GCN 5.1
STREAM PROCESSORS
4,096
COMPUTE UNITS
64
291
FAST MODELS · >30 TOK/S
Real-time chat speed
337
USABLE · >10 TOK/S
Comfortable for all tasks
337
TOTAL COMPATIBLE
Fit in VRAM at Q4
▸ DON’T WANT TO BUY?

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▸ COMPATIBLE MODELS· 337
S
Falcon-H1R Tiny 90M0.09B
FALCON·256K CTX· CHAT· REASONING
8148
TOK/S · 2% VRAM
S
SmolLM2 135M0.135B
SMOLLM·2K CTX· CHAT
5432
TOK/S · 2% VRAM
S
nomic-embed-text-v1.5 100M0.14B
EMBEDDING·8K CTX· CHAT
5238
TOK/S · 2% VRAM
S
GPT-2 124M0.14B
GPT2·1K CTX· CHAT
5238
TOK/S · 2% VRAM
S
SmolVLM 256M0.256B
SMOLLM·8K CTX· CHAT· VISION
2865
TOK/S · 2% VRAM
S
Gemma 3 270M0.27B
GEMMA·32K CTX· CHAT
2716
TOK/S · 2% VRAM
S
Snowflake Arctic Embed M v2.00.305B
EMBEDDING·8K CTX· EMBEDDING· MULTILINGUAL
2404
TOK/S · 2% VRAM
S
bge-large-en-v1.5 335M0.335B
EMBEDDING·1K CTX· CHAT
2189
TOK/S · 2% VRAM
S
mxbai-embed-large-v10.335B
EMBEDDING·1K CTX· EMBEDDING
2189
TOK/S · 2% VRAM
S
Snowflake Arctic Embed L0.335B
EMBEDDING·1K CTX· EMBEDDING
2189
TOK/S · 2% VRAM
S
LFM2 350M0.35B
LFM·125K CTX· CHAT· TOOL_USE
2095
TOK/S · 2% VRAM
S
SmolLM2 360M0.36B
SMOLLM·8K CTX· CHAT
2037
TOK/S · 2% VRAM
S
GPT-2 Medium 345M0.38B
GPT2·1K CTX· CHAT
1930
TOK/S · 2% VRAM
S
Qwen 2.5 0.5B0.5B
QWEN·32K CTX· CHAT
1467
TOK/S · 2% VRAM
S
SmolVLM 500M0.5B
SMOLLM·8K CTX· CHAT· VISION
1467
TOK/S · 2% VRAM
S
Falcon-H1 0.5B0.52B
FALCON·128K CTX· CHAT
1410
TOK/S · 3% VRAM
S
BGE-M30.568B
EMBEDDING·8K CTX· EMBEDDING
1291
TOK/S · 3% VRAM
S
Snowflake Arctic Embed L v2.00.568B
EMBEDDING·8K CTX· EMBEDDING· MULTILINGUAL
1291
TOK/S · 3% VRAM
S
Qwen3-Embedding 0.6B0.6B
EMBEDDING·32K CTX· EMBEDDING· MULTILINGUAL
1222
TOK/S · 3% VRAM
S
Falcon-H1R Tiny 0.6B0.6B
FALCON·32K CTX· CHAT· REASONING
1222
TOK/S · 3% VRAM
S
Falcon Perception 0.6B0.6B
FALCON·4K CTX· VISION
1222
TOK/S · 3% VRAM
S
Qwen 1.5 0.5B0.62B
QWEN·32K CTX· CHAT
1183
TOK/S · 3% VRAM
S
LFM2 700M0.74B
LFM·125K CTX· CHAT· TOOL_USE
991
TOK/S · 3% VRAM
S
Qwen3 0.6B0.75B
QWEN·32K CTX· CHAT· REASONING
978
TOK/S · 3% VRAM
S
GPT-2 Large 774M0.81B
GPT2·1K CTX· CHAT
905
TOK/S · 3% VRAM
S
Qwen 3.5 0.8B0.87B
QWEN·256K CTX· CHAT· CODING· MULTILINGUAL
843
TOK/S · 3% VRAM
S
InternVL3 1B0.94B
OTHER·32K CTX· CHAT· VISION
780
TOK/S · 3% VRAM
S
MiniCPM5 1B1.08B
MINICPM·128K CTX· CHAT· REASONING· MULTILINGUAL
679
TOK/S · 4% VRAM
S
TinyLlama 1.1B1.1B
LLAMA·2K CTX· CHAT
667
TOK/S · 4% VRAM
S
LFM2.5-1.2B-Thinking1.2B
LFM·122K CTX· CHAT· REASONING· TOOL_USE
611
TOK/S · 4% VRAM
S
Llama-3.2-1B1.2B
LLAMA·4K CTX· CHAT
611
TOK/S · 4% VRAM
S
LFM2 1.2B1.2B
LFM·125K CTX· CHAT· TOOL_USE· MULTILINGUAL
611
TOK/S · 4% VRAM
S
Zamba2 1.2B1.2B
OTHER·4K CTX· CHAT
611
TOK/S · 4% VRAM
S
EXAONE-4.0-1.2B1.3B
EXAONE·64K CTX· CHAT
564
TOK/S · 4% VRAM
S
OPT 1.3B1.3B
OPT·2K CTX· CHAT
564
TOK/S · 4% VRAM
S
MiniCPM-V 4.61.3B
OTHER·256K CTX· CHAT· VISION
564
TOK/S · 4% VRAM
S
DeepSeek Coder 1.3B1.35B
DEEPSEEK·16K CTX· CODING
543
TOK/S · 4% VRAM
S
Phi-1 1.3B1.42B
PHI·2K CTX· CODING
516
TOK/S · 4% VRAM
S
Phi-1.5 1.3B1.42B
PHI·2K CTX· CHAT· CODING
516
TOK/S · 4% VRAM
S
LFM2 8B A1B8.3BMoE
LFM·125K CTX· CHAT· TOOL_USE· MULTILINGUAL
489
TOK/S · 17% VRAM
▸ NEXT STEP

Get personalized recommendations.

See ranked models with benchmark scores, run commands, and precise speed estimates for your Radeon Pro Vega II.

WHAT THIS CARD IS WORTH

Radeon Pro Vega II holds 337 of the models in our catalogue and is, in practice, a Q4_K_M card — the largest it takes is Phi-3.5 MoE 42B 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
Phi-3.5 MoE 42B41.9B · Q4_K_M28.6 GB96 tok/sEST
Falcon 40B40B · Q4_K_M27.4 GB22 tok/sEST
InternVL3 38B38B · Q4_K_M26.7 GB23 tok/sEST
Seed-OSS 36B Instruct36B · Q5_K_S28.6 GB21 tok/sEST
c4ai-command-r-v01 35B35B · Q5_K_M28.1 GB21 tok/sEST
Qwen 3.5 35B A3B35B · Q5_K_M27.5 GB155 tok/sEST
Qwen 3.6 35B A3B35B · Q5_K_M27.5 GB155 tok/sEST
Nous Capybara 34B34.4B · Q5_K_M27.9 GB22 tok/sEST
AGAINST CARDS OF SIMILAR MEMORY
M4 Max (48GB)36 GB$2,4992.2 tok/s per $100
M3 Max (48GB)36 GB$2,8991.6 tok/s per $100
M4 Pro (48GB)36 GB$1,7991.9 tok/s per $100
A100 SXM4 40 GB40 GB$10,0001.4 tok/s per $100
Radeon Pro Vega II32 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

AMD Radeon Pro Vega II — 32 GB VRAM.

RADEON PRO VEGA II SPEC
BRAND
AMD
VRAM
32 GB HBM2
BANDWIDTH
825 GB/s
FP16 COMPUTE
28.2 TFLOPS
FP32 COMPUTE
14.1 TFLOPS
STREAM PROCESSORS
4,096
TDP
475 W
ARCHITECTURE
GCN 5.1
▸ AI CAPABILITY
337/ 449 models @ Q4

With 32 GB VRAM and 825 GB/s bandwidth, this GPU handles models up to 41.9B parameters.

Speed ≈ bandwidth / model_size × efficiency. A 7B model at Q4 runs at ~94 tok/s.

RENT IT — LIVE PRICES
Checking what the clouds are charging…
§ 01TOP MODELS FOR RADEON PRO VEGA II
337 FIT · SHOWING 20
MODELSIZEVRAM Q4TOK/SAVG
Phi-3.5 MoE 42B41.9B26.1 GB11156.7
Falcon 40B40B24.9 GB1820.9
InternVL3 38B38B23.7 GB1978.9
Seed-OSS 36B Instruct36B22.5 GB2054.4
c4ai-command-r-v01 35B35B21.9 GB2127.5
Qwen 3.5 35B A3B35B21.9 GB24453.3
Qwen 3.6 35B A3B35B21.9 GB24453.9
Nous Capybara 34B34.4B21.5 GB2142.0
Yi-1.5 34B34.4B21.5 GB2145.3
Falcon-H1 34B34B21.3 GB2266.1
CodeLlama 34B34B21.3 GB2225.4
Nous Hermes 2 34B34B21.3 GB2247.0
Phind CodeLlama 34B34B21.3 GB2268.1
LLaVA-1.6 Yi 34B34B21.3 GB2247.4
WizardCoder Python 34B34B21.3 GB2273.2
Yi 34B34B21.3 GB2233.4
Qwen3-VL 32B Instruct33.36B20.9 GB2244.6
DeepSeek Coder 33B33B20.7 GB2226.0
Vicuna 33B33B20.7 GB2217.2
LLaMA 1 30B33B20.7 GB2217.8