FitMyLLM
▸ NVIDIA· AMPERE

NVIDIA RTX A4500

Running LLMs on the RTX A4500 — the long read: which models fit at which quantisation, and the settings worth changing. · Or what else $2,000 buys

VRAM
20 GB
MID-RANGE
BANDWIDTH
640
GB/S
MODELS Q4
276/449
61%
7B Q4 SPEED
~73
BLAZING
▸ MODEL COVERAGE @ Q461% OF ALL
▸ ESTIMATED SPEED· BY MODEL SIZE @ Q4

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

3B
~171
TOK/S
7B
~73
TOK/S
14B
~37
TOK/S
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
20 GB
BANDWIDTH
640 GB/s
FP16 COMPUTE
23.6 TFLOPS
TDP
200W
MEMORY
GDDR6
ARCHITECTURE
Ampere
CUDA CORES
7,168
TENSOR CORES
224
PCIE
Gen 4 x16
MSRP
$2,000
263
FAST MODELS · >30 TOK/S
Real-time chat speed
276
USABLE · >10 TOK/S
Comfortable for all tasks
276
TOTAL COMPATIBLE
Fit in VRAM at Q4
▸ RENT IT IN THE CLOUD

Buying RTX A4500 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· 276
S
Falcon-H1R Tiny 90M0.09B
FALCON·256K CTX· CHAT· REASONING
5689
TOK/S · 3% VRAM
›
S
SmolLM2 135M0.135B
SMOLLM·2K CTX· CHAT
3793
TOK/S · 3% VRAM
›
S
nomic-embed-text-v1.5 100M0.14B
EMBEDDING·8K CTX· CHAT
3657
TOK/S · 3% VRAM
›
S
GPT-2 124M0.14B
GPT2·1K CTX· CHAT
3657
TOK/S · 3% VRAM
›
S
SmolVLM 256M0.256B
SMOLLM·8K CTX· CHAT· VISION
2000
TOK/S · 3% VRAM
›
S
Gemma 3 270M0.27B
GEMMA·32K CTX· CHAT
1896
TOK/S · 3% VRAM
›
S
Snowflake Arctic Embed M v2.00.305B
EMBEDDING·8K CTX· EMBEDDING· MULTILINGUAL
1679
TOK/S · 3% VRAM
›
S
bge-large-en-v1.5 335M0.335B
EMBEDDING·1K CTX· CHAT
1528
TOK/S · 3% VRAM
›
S
mxbai-embed-large-v10.335B
EMBEDDING·1K CTX· EMBEDDING
1528
TOK/S · 3% VRAM
›
S
Snowflake Arctic Embed L0.335B
EMBEDDING·1K CTX· EMBEDDING
1528
TOK/S · 3% VRAM
›
S
LFM2 350M0.35B
LFM·125K CTX· CHAT· TOOL_USE
1463
TOK/S · 4% VRAM
›
S
SmolLM2 360M0.36B
SMOLLM·8K CTX· CHAT
1422
TOK/S · 4% VRAM
›
S
GPT-2 Medium 345M0.38B
GPT2·1K CTX· CHAT
1347
TOK/S · 4% VRAM
›
S
Qwen 2.5 0.5B0.5B
QWEN·32K CTX· CHAT
1024
TOK/S · 4% VRAM
›
S
SmolVLM 500M0.5B
SMOLLM·8K CTX· CHAT· VISION
1024
TOK/S · 4% VRAM
›
S
Falcon-H1 0.5B0.52B
FALCON·128K CTX· CHAT
985
TOK/S · 4% VRAM
›
S
BGE-M30.568B
EMBEDDING·8K CTX· EMBEDDING
901
TOK/S · 4% VRAM
›
S
Snowflake Arctic Embed L v2.00.568B
EMBEDDING·8K CTX· EMBEDDING· MULTILINGUAL
901
TOK/S · 4% VRAM
›
S
Qwen3-Embedding 0.6B0.6B
EMBEDDING·32K CTX· EMBEDDING· MULTILINGUAL
853
TOK/S · 4% VRAM
›
S
Falcon-H1R Tiny 0.6B0.6B
FALCON·32K CTX· CHAT· REASONING
853
TOK/S · 4% VRAM
›
S
Falcon Perception 0.6B0.6B
FALCON·4K CTX· VISION
853
TOK/S · 4% VRAM
›
S
Qwen 1.5 0.5B0.62B
QWEN·32K CTX· CHAT
826
TOK/S · 4% VRAM
›
S
LFM2 700M0.74B
LFM·125K CTX· CHAT· TOOL_USE
692
TOK/S · 5% VRAM
›
S
Qwen3 0.6B0.75B
QWEN·32K CTX· CHAT· REASONING
683
TOK/S · 5% VRAM
›
S
GPT-2 Large 774M0.81B
GPT2·1K CTX· CHAT
632
TOK/S · 5% VRAM
›
S
Qwen 3.5 0.8B0.87B
QWEN·256K CTX· CHAT· CODING· MULTILINGUAL
589
TOK/S · 5% VRAM
›
S
InternVL3 1B0.94B
OTHER·32K CTX· CHAT· VISION
545
TOK/S · 5% VRAM
›
S
MiniCPM5 1B1.08B
MINICPM·128K CTX· CHAT· REASONING· MULTILINGUAL
474
TOK/S · 6% VRAM
›
S
TinyLlama 1.1B1.1B
LLAMA·2K CTX· CHAT
465
TOK/S · 6% VRAM
›
S
LFM2.5-1.2B-Thinking1.2B
LFM·122K CTX· CHAT· REASONING· TOOL_USE
427
TOK/S · 6% VRAM
›
S
Llama-3.2-1B1.2B
LLAMA·4K CTX· CHAT
427
TOK/S · 6% VRAM
›
S
LFM2 1.2B1.2B
LFM·125K CTX· CHAT· TOOL_USE· MULTILINGUAL
427
TOK/S · 6% VRAM
›
S
Zamba2 1.2B1.2B
OTHER·4K CTX· CHAT
427
TOK/S · 6% VRAM
›
S
EXAONE-4.0-1.2B1.3B
EXAONE·64K CTX· CHAT
394
TOK/S · 6% VRAM
›
S
OPT 1.3B1.3B
OPT·2K CTX· CHAT
394
TOK/S · 6% VRAM
›
S
MiniCPM-V 4.61.3B
OTHER·256K CTX· CHAT· VISION
394
TOK/S · 6% VRAM
›
S
DeepSeek Coder 1.3B1.35B
DEEPSEEK·16K CTX· CODING
379
TOK/S · 7% VRAM
›
S
Phi-1 1.3B1.42B
PHI·2K CTX· CODING
361
TOK/S · 7% VRAM
›
S
Phi-1.5 1.3B1.42B
PHI·2K CTX· CHAT· CODING
361
TOK/S · 7% VRAM
›
S
LFM2 8B A1B8.3BMoE
LFM·125K CTX· CHAT· TOOL_USE· MULTILINGUAL
341
TOK/S · 28% VRAM
›
▸ NEXT STEP

Get personalized recommendations.

See ranked models with benchmark scores, run commands, and precise speed estimates for your RTX A4500.

WHAT THIS CARD IS WORTH

RTX A4500 holds 276 of the models in our catalogue and is, in practice, a IQ4_XS card — the largest it takes is Qwen3.5-27B at IQ4_XS.

TOKENS/SEC PER $100
3.3
8B at Q4_K_M, so cards compare like for like
VRAM PER $100
1.00 GB
what memory costs on this card
THE BIGGEST IT TAKES
Qwen3.5-27B27.8B · IQ4_XS17.6 GB19 tok/sEST
gemma-3-27b27.4B · IQ4_XS17.8 GB19 tok/sEST
Qwen 3.6 27B27B · IQ4_XS17.8 GB20 tok/sEST
Gemma 4 26B A4B26B · IQ4_XS17.3 GB133 tok/sEST
Aria 25B A3.9B25.3B · IQ4_XS17.7 GB137 tok/sEST
Mistral-Small-24B24B · Q4_K_M17.1 GB20 tok/sEST
Mistral-Small-3.1-24B24B · Q4_K_M17.8 GB20 tok/sEST
Magistral Small 24B24B · Q4_K_M17.1 GB20 tok/sEST
AGAINST CARDS OF SIMILAR MEMORY
M3 Max (36GB)27 GB$2,4991.5 tok/s per $100
M3 Pro (36GB)27 GB$1,9991.2 tok/s per $100
M1 Max (32GB)21 GB$1,4993.0 tok/s per $100
M2 Max (32GB)21 GB$1,7992.5 tok/s per $100
RTX A450020 GB$2,0003.3 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

NVIDIA RTX A4500 — 20 GB VRAM.

▸ RTX A4500 SPEC
BRAND
NVIDIA
VRAM
20 GB GDDR6
BANDWIDTH
640 GB/s
FP16 COMPUTE
23.6 TFLOPS
FP32 COMPUTE
23.6 TFLOPS
CUDA CORES
7,168
TENSOR CORES
224
TDP
200 W
ARCHITECTURE
Ampere
MSRP
$2000
▸ AI CAPABILITY
276/ 449 models @ Q4

With 20 GB VRAM and 640 GB/s bandwidth, this GPU handles models up to 24B parameters.

Speed ≈ bandwidth / model_size × efficiency. A 7B model at Q4 runs at ~73 tok/s.

RENT IT — LIVE PRICES
Checking what the clouds are charging…
§ 01TOP MODELS FOR RTX A4500
276 FIT · SHOWING 20
MODELSIZEVRAM Q4TOK/SAVG
Mistral-Small-24B24B15.2 GB2125.0
Mistral-Small-3.1-24B24B15.2 GB2128.8
Magistral Small 24B24B15.2 GB2147.0
Devstral Small 2 24B24B15.2 GB2133.4
Mistral-Small-3.2-24B24B15.2 GB2144.4
LFM2 24B A2B24B15.2 GB25619.1
Devstral Small 22B23.57B14.9 GB2235.5
Codestral 22B22.2B14.1 GB2350.1
Mistral Small 22B22.2B14.1 GB2335.2
SOLAR-Pro 22B22.1B14.0 GB2344.2
ERNIE 4.5 21B A3B21.95B13.9 GB171—
GPT-OSS 20B21B13.3 GB14252.9
Reka Flash 321B13.3 GB2436.2
Reka Flash 3.121B13.3 GB2433.4
InternLM2 20B19.8B12.6 GB2645.1
InternLM2.5 20B19.8B12.6 GB2650.9
Ling-lite 16.8B16.8B10.8 GB213—
DeepSeek V2 Lite 16B16B10.3 GB21338.0
StarCoder2 15B15.96B10.2 GB3226.5
DeepSeek-Coder-V2-Lite 15.7B15.7B10.1 GB21343.0