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All estimates are approximations based on mathematical models and public specifications. Actual performance may vary. Do not make purchasing decisions based solely on these estimates.

Data sourced from Hugging Face, Ollama, and official model documentation. Model names and logos are trademarks of their respective owners.

© 2026 Will It Run AI — Fase Consulting Ibiza, S.L. (NIF: B57969656)

Home/Hardware/GPUs/Radeon Pro W7500 8GB
AMD

AMD

Radeon Pro W7500 8GB

Radeon ProWorkstationRDNA 3PCIe 4ROCm
8GB
VRAM
224GB/s
Bandwidth
17TFLOPS
FP16 Compute
136TOPS
INT8 Inference
VRAM8 GBBandwidth224 GB/sCompute17 TFInference136 TOPS
Radeon Pro W7500 8GBCategory AvgIntel Arc B570 10GB

Specifications

Compute
FP1617 TFLOPS
INT8136 TOPS
ArchitectureRDNA 3
Memory
VRAM8 GB
Bandwidth224 GB/s
General
FamilyRadeon Pro
SegmentWorkstation
InterconnectPCIe 4
Compute PlatformROCM

Architecture

RDNA 3

RDNA 3 is AMD's chiplet-based GPU architecture, combining a 5nm Graphics Compute Die (GCD) with 6nm Memory Cache Dies (MCDs). It introduces AI accelerators and a new unified compute unit design.

AI Relevance

ROCm support for RDNA 3 is maturing but lags behind NVIDIA's CUDA ecosystem. AI accelerator units provide some inference acceleration, but lack the dedicated Tensor Core equivalent found in NVIDIA GPUs.

Process: TSMC 5nm + 6nmPlatform: ROCMPrecisions: FP32, FP16, BF16, INT8

Recommendations by Workload

Agentic Coding

C

StarCoder2 3B

This model is still usable for agentic-coding, but it is not the most specialized pick. It sits in the middle of the current model mix. It fits natively with comfortable headroom.

Decode 72.2 tok/s · 57K ctx · llama.cpp
4.5 GB / 8.0 GB VRAM

Chat

C

Qwen 3 4B

This model is a direct match for chat. It sits in the middle of the current model mix. It fits natively with comfortable headroom. Known channels: huggingface, ollama, lm-studio.

Decode 54.2 tok/s · 13K ctx · llama.cpp
4.9 GB / 8.0 GB VRAM

Coding

C

Codestral Mamba 7B

This model is still usable for coding, but it is not the most specialized pick. It sits in the middle of the current model mix. It should run, but memory headroom will be limited. Known channels: huggingface, ollama.

Decode 31.0 tok/s · 18K ctx · llama.cpp
7.1 GB / 8.0 GB VRAM

RAG

C

Phi 4 Mini 4B

This model is still usable for rag, but it is not the most specialized pick. It belongs to a current frontier family for local AI. It fits natively with comfortable headroom. Known channels: huggingface, ollama, lm-studio.

Decode 54.2 tok/s · 47K ctx · llama.cpp
5.4 GB / 8.0 GB VRAM

Reasoning

C

Phi 4 Mini 4B

This model is a direct match for reasoning. It belongs to a current frontier family for local AI. It fits natively with comfortable headroom. Known channels: huggingface, ollama, lm-studio.

Decode 54.2 tok/s · 26K ctx · llama.cpp
4.9 GB / 8.0 GB VRAM

Full Model Compatibility

UnslothQwen3.5 4B
C54
4B4.9 GB54 tok/s26K ctx
dense
BartowskiBLlama 3.2 3B Instruct
C54
3B4.7 GB62 tok/s27K ctx
dense
Lmstudio-communityLgemma 3 4b it
C54
4B4.9 GB54 tok/s26K ctx
dense
BartowskiBgemma 2 2b it
C53
2B4.1 GB85 tok/s31K ctx
dense
QwenQwen2.5 3B Instruct
C53
3B4.3 GB72 tok/s30K ctx
dense
Googlegemma 2b
C52
2B3.7 GB108 tok/s34K ctx
dense
TheDrummerTGemmasutra Mini 2B v1
C52
2B3.7 GB108 tok/s34K ctx
dense
QwenQwen2.5 1.5B Instruct
C51
1.5B3.4 GB132 tok/s37K ctx
dense
Hugging-quantsHLlama 3.2 1B Instruct Q8 0
C51
1B3.3 GB139 tok/s39K ctx
dense
TheBlokeTTinyLlama 1.1B Chat v1.0
C51
1.1B3.2 GB132 tok/s40K ctx
dense
TheBlokeTLlama 2 7B Chat
C51
7B7.1 GB31 tok/s18K ctx
dense
TheBlokeTMistral 7B Instruct v0.2
C51
7B7.1 GB31 tok/s18K ctx
dense
MaziyarPanahiMMistral 7B Instruct v0.3
C51
7B7.1 GB31 tok/s18K ctx
dense
BartowskiBMeta Llama 3.1 8B Instruct
C50
8B7.8 GB27 tok/s16K ctx
dense
XtunerXllava llama 3 8b v1 1
C50
8B7.8 GB27 tok/s16K ctx
dense
UnslothDeepSeek R1 0528 Qwen3 8B
C50
8B7.8 GB27 tok/s16K ctx
dense
MaziyarPanahiMMeta Llama 3 8B Instruct
C50
8B7.8 GB27 tok/s16K ctx
dense
Ggml-orgGSmolVLM 500M Instruct
C50
0.5B2.9 GB139 tok/s44K ctx
dense
Ggml-orgGembeddinggemma 300M
C49
0.3B2.7 GB139 tok/s47K ctx
dense
UnslothQwen3.5 9B
D40
9B8.6 GB23 tok/s15K ctx
dense
HauhauCSHQwen3.5 9B Uncensored HauhauCS Aggressive
D40
9B8.6 GB23 tok/s15K ctx
dense
Lmstudio-communityLQwen3.5 9B
D40
9B8.6 GB23 tok/s15K ctx
dense
DeepSeekDeepSeek R1 671B
F0
671B416.8 GB2 tok/s4K ctx
moe
MistralDevstral 2 123B Instruct
F0
123B95.9 GB2 tok/s4K ctx
dense
Z.aiGLM-5
F0
744B461.8 GB2 tok/s4K ctx
moe
UnslothQwen3.5 27B
F0
27B22.4 GB8 tok/s6K ctx
dense
UnslothQwen3.5 35B A3B
F0
35B28.5 GB6 tok/s4K ctx
dense
Moonshot AIKimi K2.5
F0
1000B616.7 GB2 tok/s4K ctx
moe
MistralMistral Large 3
F0
675B419.9 GB2 tok/s4K ctx
+1moe
MistralMistral Small 4 119B
F0
119B75.3 GB5 tok/s4K ctx
moe
AlibabaQwen3-Coder 30B A3B Instruct
F0
30.5B21.1 GB18 tok/s6K ctx
moe
AlibabaQwen3-Coder 480B A35B Instruct
F0
480B300.0 GB2 tok/s4K ctx
moe
AlibabaQwen3-Coder-Next
F0
80B51.3 GB8 tok/s4K ctx
moe
UnslothQwen3.5 122B A10B
F0
122B80.5 GB2 tok/s4K ctx
dense
DeepSeekDeepSeek V3 671B
F0
671B416.8 GB2 tok/s4K ctx
moe
MistralMixtral 8x22B
F0
141B93.8 GB3 tok/s4K ctx
moe
AlibabaQwen 2.5 72B
F0
72B56.9 GB3 tok/s4K ctx
dense
AlibabaQwen 3 235B A22B
F0
235B148.5 GB3 tok/s4K ctx
moe
AlibabaQwen3-VL 30B A3B Instruct
F0
30B20.8 GB19 tok/s6K ctx
moe
UnslothQwen3.5 397B A17B
F0
397B305.9 GB2 tok/s4K ctx
dense
MistralDevstral Small 2 24B Instruct
F0
24B20.1 GB9 tok/s6K ctx
dense
MetaLlama 3.3 70B
F0
70B55.3 GB3 tok/s4K ctx
dense
MetaLlama 4 Maverick 17B 128E
F0
400B248.4 GB2 tok/s4K ctx
moe
CohereCommand A 111B
F0
111B86.8 GB2 tok/s4K ctx
dense
AlibabaQwen 2.5 Coder 32B
F0
32B26.2 GB7 tok/s5K ctx
dense
AlibabaQwen 2.5 VL 72B
F0
72B56.9 GB3 tok/s4K ctx
dense
Unslothgemma 3 27b it
F0
27B22.4 GB8 tok/s6K ctx
dense
Lmstudio-communityLQwen3.5 35B A3B
F0
35B28.5 GB6 tok/s4K ctx
dense
MistralCodestral 2 25.08
F0
22B18.6 GB10 tok/s7K ctx
dense
MistralDevstral Small 1.1
F0
24B20.1 GB9 tok/s6K ctx
dense

Just out of reach

Models you could run with an upgrade

High-quality models that need a bit more memory

DeepSeekDeepSeek R1 671B
671BTier 5Needs ~422.6 GB
MistralDevstral 2 123B Instruct
123BTier 5Needs ~115.2 GB
Runs on Mac Studio M3 Ultra 256GB
Z.aiGLM-5
744BTier 5Needs ~468.0 GB
UnslothQwen3.5 27B
27BTier 5Needs ~26.6 GB
Runs on RTX 5090 32GB (~$1,999)
UnslothQwen3.5 35B A3B
35BTier 5Needs ~34.0 GB
Runs on Mac mini M4 64GB (~$1,099)

Upgrade paths

Upgrade from Radeon Pro W7500 8GB

See what you unlock with more powerful hardware

Upgrade options

Upgrade options

IntelIntel Arc B570 10GBNext step up
10 GB VRAM (+2)380 GB/s (+156)
A
Unlocks Qwen3.5 9B, Qwen3.5 9B Uncensored HauhauCS Aggressive, Qwen3.5 9B+20 more · +46% faster avg

 

AMDRX 6750 XT 12GBAMD upgrade
12 GB VRAM (+4)432 GB/s (+208)
A
Unlocks Qwen3.5 9B, Qwen3.5 9B Uncensored HauhauCS Aggressive, Qwen3.5 9B+31 more · +58% faster avg

 

AMDRX 7600 XT 16GBBest value
16 GB VRAM (+8)288 GB/s (+64)
A
Unlocks Qwen3.5 9B, Qwen3.5 9B Uncensored HauhauCS Aggressive, Qwen3.5 9B+57 more · +6% faster avg

~$329 MSRP

AMDAMD Instinct MI350X 288GBBiggest leap
288 GB VRAM (+280)8000 GB/s (+7776)
A
Unlocks Devstral 2 123B Instruct, Qwen3.5 27B, Qwen3.5 35B A3B+141 more · +2787% faster avg

~$8,000 MSRP

Compare this GPU