FitMyLLM
AMD· GCN 3.0

AMD FirePro S7100X

Running LLMs on the FirePro S7100X — the long read: which models fit at which quantisation, and the settings worth changing. · Or what a budget buys

VRAM
8 GB
ENTRY-LEVEL
BANDWIDTH
160
GB/S
MODELS Q4
201/449
45%
7B Q4 SPEED
~20
GOOD
▸ MODEL COVERAGE @ Q445% OF ALL
▸ ESTIMATED SPEED· BY MODEL SIZE @ Q4

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

3B
~47
TOK/S
7B
~20
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
8 GB
BANDWIDTH
160 GB/s
FP16 COMPUTE
3 TFLOPS
TDP
100W
MEMORY
GDDR5
ARCHITECTURE
GCN 3.0
STREAM PROCESSORS
2,048
PCIE
Gen 3 x16
107
FAST MODELS · >30 TOK/S
Real-time chat speed
201
USABLE · >10 TOK/S
Comfortable for all tasks
201
TOTAL COMPATIBLE
Fit in VRAM at Q4
▸ DON’T WANT TO BUY?

Test FirePro S7100X (or anything bigger) without committing. Pay by the second, cancel anytime.

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· 201
S
Falcon-H1R Tiny 90M0.09B
FALCON·256K CTX· CHAT· REASONING
1580
TOK/S · 7% VRAM
S
SmolLM2 135M0.135B
SMOLLM·2K CTX· CHAT
1053
TOK/S · 7% VRAM
S
nomic-embed-text-v1.5 100M0.14B
EMBEDDING·8K CTX· CHAT
1016
TOK/S · 7% VRAM
S
GPT-2 124M0.14B
GPT2·1K CTX· CHAT
1016
TOK/S · 7% VRAM
S
SmolVLM 256M0.256B
SMOLLM·8K CTX· CHAT· VISION
556
TOK/S · 8% VRAM
S
Gemma 3 270M0.27B
GEMMA·32K CTX· CHAT
527
TOK/S · 8% VRAM
S
Snowflake Arctic Embed M v2.00.305B
EMBEDDING·8K CTX· EMBEDDING· MULTILINGUAL
466
TOK/S · 8% VRAM
S
bge-large-en-v1.5 335M0.335B
EMBEDDING·1K CTX· CHAT
425
TOK/S · 9% VRAM
S
mxbai-embed-large-v10.335B
EMBEDDING·1K CTX· EMBEDDING
425
TOK/S · 9% VRAM
S
Snowflake Arctic Embed L0.335B
EMBEDDING·1K CTX· EMBEDDING
425
TOK/S · 9% VRAM
S
LFM2 350M0.35B
LFM·125K CTX· CHAT· TOOL_USE
406
TOK/S · 9% VRAM
S
SmolLM2 360M0.36B
SMOLLM·8K CTX· CHAT
395
TOK/S · 9% VRAM
S
GPT-2 Medium 345M0.38B
GPT2·1K CTX· CHAT
374
TOK/S · 9% VRAM
S
Qwen 2.5 0.5B0.5B
QWEN·32K CTX· CHAT
284
TOK/S · 10% VRAM
S
SmolVLM 500M0.5B
SMOLLM·8K CTX· CHAT· VISION
284
TOK/S · 10% VRAM
S
Falcon-H1 0.5B0.52B
FALCON·128K CTX· CHAT
274
TOK/S · 10% VRAM
S
BGE-M30.568B
EMBEDDING·8K CTX· EMBEDDING
250
TOK/S · 10% VRAM
S
Snowflake Arctic Embed L v2.00.568B
EMBEDDING·8K CTX· EMBEDDING· MULTILINGUAL
250
TOK/S · 10% VRAM
S
Qwen3-Embedding 0.6B0.6B
EMBEDDING·32K CTX· EMBEDDING· MULTILINGUAL
237
TOK/S · 11% VRAM
S
Falcon-H1R Tiny 0.6B0.6B
FALCON·32K CTX· CHAT· REASONING
237
TOK/S · 11% VRAM
S
Falcon Perception 0.6B0.6B
FALCON·4K CTX· VISION
237
TOK/S · 11% VRAM
S
Qwen 1.5 0.5B0.62B
QWEN·32K CTX· CHAT
229
TOK/S · 11% VRAM
S
LFM2 700M0.74B
LFM·125K CTX· CHAT· TOOL_USE
192
TOK/S · 12% VRAM
S
Qwen3 0.6B0.75B
QWEN·32K CTX· CHAT· REASONING
190
TOK/S · 12% VRAM
S
GPT-2 Large 774M0.81B
GPT2·1K CTX· CHAT
176
TOK/S · 12% VRAM
S
Qwen 3.5 0.8B0.87B
QWEN·256K CTX· CHAT· CODING· MULTILINGUAL
163
TOK/S · 13% VRAM
S
InternVL3 1B0.94B
OTHER·32K CTX· CHAT· VISION
151
TOK/S · 13% VRAM
S
MiniCPM5 1B1.08B
MINICPM·128K CTX· CHAT· REASONING· MULTILINGUAL
132
TOK/S · 14% VRAM
S
TinyLlama 1.1B1.1B
LLAMA·2K CTX· CHAT
129
TOK/S · 15% VRAM
S
LFM2.5-1.2B-Thinking1.2B
LFM·122K CTX· CHAT· REASONING· TOOL_USE
119
TOK/S · 15% VRAM
S
Llama-3.2-1B1.2B
LLAMA·4K CTX· CHAT
119
TOK/S · 15% VRAM
S
LFM2 1.2B1.2B
LFM·125K CTX· CHAT· TOOL_USE· MULTILINGUAL
119
TOK/S · 15% VRAM
S
Zamba2 1.2B1.2B
OTHER·4K CTX· CHAT
119
TOK/S · 15% VRAM
S
EXAONE-4.0-1.2B1.3B
EXAONE·64K CTX· CHAT
109
TOK/S · 16% VRAM
S
OPT 1.3B1.3B
OPT·2K CTX· CHAT
109
TOK/S · 16% VRAM
S
MiniCPM-V 4.61.3B
OTHER·256K CTX· CHAT· VISION
109
TOK/S · 16% VRAM
S
DeepSeek Coder 1.3B1.35B
DEEPSEEK·16K CTX· CODING
105
TOK/S · 16% VRAM
S
Phi-1 1.3B1.42B
PHI·2K CTX· CODING
100
TOK/S · 17% VRAM
S
Phi-1.5 1.3B1.42B
PHI·2K CTX· CHAT· CODING
100
TOK/S · 17% VRAM
S
LFM2 8B A1B8.3BMoE
LFM·125K CTX· CHAT· TOOL_USE· MULTILINGUAL
95
TOK/S · 70% VRAM
▸ NEXT STEP

Get personalized recommendations.

See ranked models with benchmark scores, run commands, and precise speed estimates for your FirePro S7100X.

WHAT THIS CARD IS WORTH

FirePro S7100X holds 201 of the models in our catalogue and is, in practice, a IQ4_XS card — the largest it takes is Falcon3-10B at IQ4_XS.

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
Falcon3-10B10.3B · IQ4_XS7.1 GB15 tok/sEST
Bamba 9B v29.78B · Q4_K_M7.2 GB14 tok/sEST
RecurrentGemma 9B9.63B · Q4_K_M6.8 GB14 tok/sEST
glm-4-9b9.4B · Q4_K_M6.6 GB15 tok/sEST
Yi 1.5 9B9B · Q4_K_M6.5 GB15 tok/sEST
Yi Coder 9B9B · Q4_K_M6.5 GB15 tok/sEST
Ministral 3 8B8.92B · Q4_K_M6.6 GB15 tok/sEST
Ministral 3 8B Reasoning8.92B · Q4_K_M6.6 GB15 tok/sEST
AGAINST CARDS OF SIMILAR MEMORY
M3 Pro (18GB)12 GB$1,5991.5 tok/s per $100
M1 Pro (16GB)11 GB$9992.9 tok/s per $100
M2 Pro (16GB)11 GB$1,2992.2 tok/s per $100
M4 (16GB)11 GB$4994.0 tok/s per $100
FirePro S7100X8 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 FirePro S7100X — 8 GB VRAM.

FIREPRO S7100X SPEC
BRAND
AMD
VRAM
8 GB GDDR5
BANDWIDTH
160 GB/s
FP16 COMPUTE
3 TFLOPS
FP32 COMPUTE
3 TFLOPS
STREAM PROCESSORS
2,048
TDP
100 W
ARCHITECTURE
GCN 3.0
▸ AI CAPABILITY
201/ 449 models @ Q4

With 8 GB VRAM and 160 GB/s bandwidth, this GPU handles models up to 9.63B parameters.

Speed ≈ bandwidth / model_size × efficiency. A 7B model at Q4 runs at ~18 tok/s.

RENT IT — LIVE PRICES
Checking what the clouds are charging…
§ 01TOP MODELS FOR FIREPRO S7100X
201 FIT · SHOWING 20
MODELSIZEVRAM Q4TOK/SAVG
RecurrentGemma 9B9.63B6.4 GB1535.0
glm-4-9b9.4B6.2 GB1520.5
gemma-2-9b9.2B6.1 GB1530.2
Yi 1.5 9B9B6.0 GB1630.3
Yi Coder 9B9B6.0 GB1635.8
Ministral 3 8B8.92B5.9 GB1625.7
Ministral 3 8B Reasoning8.92B5.9 GB16
NVIDIA-Nemotron-Nano-9B-v28.9B5.9 GB1644.2
InternLM3 8B Instruct8.8B5.9 GB1638.7
Gemma 1 7B8.54B5.7 GB1724.7
CodeGemma 7B8.54B5.7 GB1740.2
LFM2 8B A1B8.3B5.6 GB9524.3
Seed-Coder 8B Instruct8.25B5.5 GB1734.1
Seed-Coder 8B Reasoning8.25B5.5 GB1732.9
DeepSeek R1-0528 Qwen3 8B8.2B5.5 GB1736.3
Qwen3-8B8.2B5.5 GB1743.3
Granite 3.0 8B8.17B5.5 GB1736.4
Granite 3.1 8B8.17B5.5 GB1738.6
Command-R7B8.03B5.4 GB1835.3
Aya Expanse 8B8B5.4 GB1827.8