FitMyLLM
AMD· GCN 5.0

AMD Atari VCS 400 GPU

Running LLMs on the Atari VCS 400 GPU — the long read: which models fit at which quantisation, and the settings worth changing. · Or what a budget buys

VRAM
4 GB
BUDGET
BANDWIDTH
38
GB/S
MODELS Q4
97/449
22%
7B Q4 SPEED
~5
SLOW
▸ MODEL COVERAGE @ Q422% OF ALL
▸ ESTIMATED SPEED· BY MODEL SIZE @ Q4

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

3B
~11
TOK/S
7B
3.9GB NEEDED
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
4 GB
BANDWIDTH
38 GB/s
FP16 COMPUTE
0.9 TFLOPS
TDP
15W
MEMORY
DDR4
ARCHITECTURE
GCN 5.0
STREAM PROCESSORS
192
COMPUTE UNITS
3
29
FAST MODELS · >30 TOK/S
Real-time chat speed
86
USABLE · >10 TOK/S
Comfortable for all tasks
97
TOTAL COMPATIBLE
Fit in VRAM at Q4
▸ DON’T WANT TO BUY?

Test Atari VCS 400 GPU (or anything bigger) without committing. Pay by the second, cancel anytime.

Spin up in ~60s. Pay by the second. Cancel anytime.

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▸ COMPATIBLE MODELS· 97
S
Falcon-H1R Tiny 90M0.09B
FALCON·256K CTX· CHAT· REASONING
375
TOK/S · 14% VRAM
S
SmolLM2 135M0.135B
SMOLLM·2K CTX· CHAT
250
TOK/S · 14% VRAM
S
nomic-embed-text-v1.5 100M0.14B
EMBEDDING·8K CTX· CHAT
241
TOK/S · 14% VRAM
S
GPT-2 124M0.14B
GPT2·1K CTX· CHAT
241
TOK/S · 14% VRAM
S
SmolVLM 256M0.256B
SMOLLM·8K CTX· CHAT· VISION
132
TOK/S · 16% VRAM
S
Gemma 3 270M0.27B
GEMMA·32K CTX· CHAT
125
TOK/S · 16% VRAM
S
Snowflake Arctic Embed M v2.00.305B
EMBEDDING·8K CTX· EMBEDDING· MULTILINGUAL
111
TOK/S · 17% VRAM
S
bge-large-en-v1.5 335M0.335B
EMBEDDING·1K CTX· CHAT
101
TOK/S · 17% VRAM
S
mxbai-embed-large-v10.335B
EMBEDDING·1K CTX· EMBEDDING
101
TOK/S · 17% VRAM
S
Snowflake Arctic Embed L0.335B
EMBEDDING·1K CTX· EMBEDDING
101
TOK/S · 17% VRAM
S
LFM2 350M0.35B
LFM·125K CTX· CHAT· TOOL_USE
97
TOK/S · 18% VRAM
S
SmolLM2 360M0.36B
SMOLLM·8K CTX· CHAT
94
TOK/S · 18% VRAM
S
GPT-2 Medium 345M0.38B
GPT2·1K CTX· CHAT
89
TOK/S · 18% VRAM
S
Qwen 2.5 0.5B0.5B
QWEN·32K CTX· CHAT
68
TOK/S · 20% VRAM
S
SmolVLM 500M0.5B
SMOLLM·8K CTX· CHAT· VISION
68
TOK/S · 20% VRAM
S
Falcon-H1 0.5B0.52B
FALCON·128K CTX· CHAT
65
TOK/S · 20% VRAM
A
BGE-M30.568B
EMBEDDING·8K CTX· EMBEDDING
59
TOK/S · 21% VRAM
A
Snowflake Arctic Embed L v2.00.568B
EMBEDDING·8K CTX· EMBEDDING· MULTILINGUAL
59
TOK/S · 21% VRAM
A
Qwen3-Embedding 0.6B0.6B
EMBEDDING·32K CTX· EMBEDDING· MULTILINGUAL
56
TOK/S · 21% VRAM
A
Falcon-H1R Tiny 0.6B0.6B
FALCON·32K CTX· CHAT· REASONING
56
TOK/S · 21% VRAM
A
Falcon Perception 0.6B0.6B
FALCON·4K CTX· VISION
56
TOK/S · 21% VRAM
A
Qwen 1.5 0.5B0.62B
QWEN·32K CTX· CHAT
54
TOK/S · 22% VRAM
A
LFM2 700M0.74B
LFM·125K CTX· CHAT· TOOL_USE
46
TOK/S · 24% VRAM
A
Qwen3 0.6B0.75B
QWEN·32K CTX· CHAT· REASONING
45
TOK/S · 24% VRAM
A
GPT-2 Large 774M0.81B
GPT2·1K CTX· CHAT
42
TOK/S · 25% VRAM
B
Qwen 3.5 0.8B0.87B
QWEN·256K CTX· CHAT· CODING· MULTILINGUAL
39
TOK/S · 26% VRAM
B
InternVL3 1B0.94B
OTHER·32K CTX· CHAT· VISION
36
TOK/S · 27% VRAM
B
TinyLlama 1.1B1.1B
LLAMA·2K CTX· CHAT
31
TOK/S · 29% VRAM
B
MiniCPM5 1B1.08B
MINICPM·128K CTX· CHAT· REASONING· MULTILINGUAL
31
TOK/S · 29% VRAM
B
LFM2.5-1.2B-Thinking1.2B
LFM·122K CTX· CHAT· REASONING· TOOL_USE
28
TOK/S · 31% VRAM
B
Llama-3.2-1B1.2B
LLAMA·4K CTX· CHAT
28
TOK/S · 31% VRAM
B
LFM2 1.2B1.2B
LFM·125K CTX· CHAT· TOOL_USE· MULTILINGUAL
28
TOK/S · 31% VRAM
B
Zamba2 1.2B1.2B
OTHER·4K CTX· CHAT
28
TOK/S · 31% VRAM
B
EXAONE-4.0-1.2B1.3B
EXAONE·64K CTX· CHAT
26
TOK/S · 32% VRAM
B
OPT 1.3B1.3B
OPT·2K CTX· CHAT
26
TOK/S · 32% VRAM
B
MiniCPM-V 4.61.3B
OTHER·256K CTX· CHAT· VISION
26
TOK/S · 32% VRAM
B
DeepSeek Coder 1.3B1.35B
DEEPSEEK·16K CTX· CODING
25
TOK/S · 33% VRAM
C
Phi-1 1.3B1.42B
PHI·2K CTX· CODING
24
TOK/S · 34% VRAM
C
Phi-1.5 1.3B1.42B
PHI·2K CTX· CHAT· CODING
24
TOK/S · 34% VRAM
C
Qwen2.5-Coder-1.5B1.5B
QWEN·32K CTX· CHAT· TOOL_USE· CODING
23
TOK/S · 35% VRAM
▸ NEXT STEP

Get personalized recommendations.

See ranked models with benchmark scores, run commands, and precise speed estimates for your Atari VCS 400 GPU.

WHAT THIS CARD IS WORTH

Atari VCS 400 GPU holds 97 of the models in our catalogue and is, in practice, a Q4_K_M card — the largest it takes is InternLM2 5B 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
InternLM2 5B4.5B · Q4_K_M3.6 GB6 tok/sEST
Ministral 3 3B Reasoning4.25B · Q4_K_M3.3 GB6 tok/sEST
Qwen3 4B4B · Q4_K_M3.3 GB7 tok/sEST
Qwen3-4B Instruct 25074B · Q4_K_M3.3 GB7 tok/sEST
Qwen3-Embedding 4B4B · Q4_K_M3.3 GB7 tok/sEST
Nemotron 3 Nano 4B3.97B · Q4_K_M3.4 GB7 tok/sEST
Ministral 3 3B3.85B · Q5_K_M3.5 GB6 tok/sEST
phi-3-mini-4k 3.8B3.8B · Q4_K_M3.4 GB7 tok/sEST
AGAINST CARDS OF SIMILAR MEMORY
RTX 3070 Ti8 GB$49912.6 tok/s per $100
RTX 3060 Ti GDDR6X8 GB$39915.8 tok/s per $100
RTX 3070 Ti 8 GB GA1028 GB$59910.5 tok/s per $100
Arc A7508 GB$19910.1 tok/s per $100
Atari VCS 400 GPU4 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 Atari VCS 400 GPU — 4 GB VRAM.

ATARI VCS 400 GPU SPEC
BRAND
AMD
VRAM
4 GB DDR4
BANDWIDTH
38 GB/s
FP16 COMPUTE
0.9 TFLOPS
FP32 COMPUTE
0.5 TFLOPS
STREAM PROCESSORS
192
TDP
15 W
ARCHITECTURE
GCN 5.0
▸ AI CAPABILITY
97/ 449 models @ Q4

With 4 GB VRAM and 38 GB/s bandwidth, this GPU handles models up to 4.25B parameters.

Speed ≈ bandwidth / model_size × efficiency. A 7B model at Q4 runs at ~4 tok/s.

§ 01TOP MODELS FOR ATARI VCS 400 GPU
97 FIT · SHOWING 20
MODELSIZEVRAM Q4TOK/SAVG
Ministral 3 3B Reasoning4.25B3.1 GB8
Qwen 1.5 4B4B2.9 GB812.6
Qwen3 4B4B2.9 GB840.7
Qwen3-4B Instruct 25074B2.9 GB837.2
Qwen3-Embedding 4B4B2.9 GB8
Nemotron 3 Nano 4B3.97B2.9 GB932.0
Ministral 3 3B3.85B2.8 GB921.4
Phi-3.5 Mini 3.8B3.82B2.8 GB946.6
phi-3-mini-4k 3.8B3.8B2.8 GB930.5
Phi-4-mini 3.8B3.8B2.8 GB949.0
Cogito 3B3.61B2.7 GB922.1
Falcon3-3B3.23B2.5 GB1025.7
granite-4.0-h-micro 3.2B3.2B2.4 GB1118.4
Llama-3.2-3B3.2B2.4 GB1117.9
Falcon-H1 3B3.15B2.4 GB1149.5
Qwen 2.5 3B3.1B2.4 GB1137.2
SmolLM3-3B3.1B2.4 GB1130.5
Ministral 3B3B2.3 GB1129.6
StarCoder2 3B3B2.3 GB119.5
Granite 4.1 3B3B2.3 GB1116.6