FitMyLLM
NVIDIA· TURING

NVIDIA GeForce MX550

Running LLMs on the GeForce MX550 — the long read: which models fit at which quantisation, and the settings worth changing. · Or what a budget buys

VRAM
2 GB
BUDGET
BANDWIDTH
96
GB/S
MODELS Q4
47/449
10%
7B Q4 SPEED
~11
USABLE
▸ MODEL COVERAGE @ Q410% OF ALL
▸ ESTIMATED SPEED· BY MODEL SIZE @ Q4

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

3B
1.7GB NEEDED
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
2 GB
BANDWIDTH
96 GB/s
FP16 COMPUTE
2.7 TFLOPS
TDP
25W
MEMORY
GDDR6
ARCHITECTURE
Turing
CUDA CORES
1,024
PCIE
Gen 4 x8
47
FAST MODELS · >30 TOK/S
Real-time chat speed
47
USABLE · >10 TOK/S
Comfortable for all tasks
47
TOTAL COMPATIBLE
Fit in VRAM at Q4
▸ DON’T WANT TO BUY?

Test GeForce MX550 (or anything bigger) without committing. Pay by the second, cancel anytime.

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▸ COMPATIBLE MODELS· 47
S
Falcon-H1R Tiny 90M0.09B
FALCON·256K CTX· CHAT· REASONING
853
TOK/S · 27% VRAM
S
SmolLM2 135M0.135B
SMOLLM·2K CTX· CHAT
569
TOK/S · 29% VRAM
S
nomic-embed-text-v1.5 100M0.14B
EMBEDDING·8K CTX· CHAT
549
TOK/S · 29% VRAM
S
GPT-2 124M0.14B
GPT2·1K CTX· CHAT
549
TOK/S · 29% VRAM
S
SmolVLM 256M0.256B
SMOLLM·8K CTX· CHAT· VISION
300
TOK/S · 32% VRAM
S
Gemma 3 270M0.27B
GEMMA·32K CTX· CHAT
284
TOK/S · 33% VRAM
S
Snowflake Arctic Embed M v2.00.305B
EMBEDDING·8K CTX· EMBEDDING· MULTILINGUAL
252
TOK/S · 34% VRAM
S
bge-large-en-v1.5 335M0.335B
EMBEDDING·1K CTX· CHAT
229
TOK/S · 35% VRAM
S
mxbai-embed-large-v10.335B
EMBEDDING·1K CTX· EMBEDDING
229
TOK/S · 35% VRAM
S
Snowflake Arctic Embed L0.335B
EMBEDDING·1K CTX· EMBEDDING
229
TOK/S · 35% VRAM
S
LFM2 350M0.35B
LFM·125K CTX· CHAT· TOOL_USE
219
TOK/S · 35% VRAM
S
SmolLM2 360M0.36B
SMOLLM·8K CTX· CHAT
213
TOK/S · 35% VRAM
S
GPT-2 Medium 345M0.38B
GPT2·1K CTX· CHAT
202
TOK/S · 36% VRAM
S
Qwen 2.5 0.5B0.5B
QWEN·32K CTX· CHAT
154
TOK/S · 40% VRAM
S
SmolVLM 500M0.5B
SMOLLM·8K CTX· CHAT· VISION
154
TOK/S · 40% VRAM
S
Falcon-H1 0.5B0.52B
FALCON·128K CTX· CHAT
148
TOK/S · 40% VRAM
S
BGE-M30.568B
EMBEDDING·8K CTX· EMBEDDING
135
TOK/S · 42% VRAM
S
Snowflake Arctic Embed L v2.00.568B
EMBEDDING·8K CTX· EMBEDDING· MULTILINGUAL
135
TOK/S · 42% VRAM
S
Qwen3-Embedding 0.6B0.6B
EMBEDDING·32K CTX· EMBEDDING· MULTILINGUAL
128
TOK/S · 43% VRAM
S
Falcon-H1R Tiny 0.6B0.6B
FALCON·32K CTX· CHAT· REASONING
128
TOK/S · 43% VRAM
S
Falcon Perception 0.6B0.6B
FALCON·4K CTX· VISION
128
TOK/S · 43% VRAM
S
Qwen 1.5 0.5B0.62B
QWEN·32K CTX· CHAT
124
TOK/S · 43% VRAM
S
LFM2 700M0.74B
LFM·125K CTX· CHAT· TOOL_USE
104
TOK/S · 47% VRAM
S
Qwen3 0.6B0.75B
QWEN·32K CTX· CHAT· REASONING
102
TOK/S · 47% VRAM
S
GPT-2 Large 774M0.81B
GPT2·1K CTX· CHAT
95
TOK/S · 49% VRAM
S
Qwen 3.5 0.8B0.87B
QWEN·256K CTX· CHAT· CODING· MULTILINGUAL
88
TOK/S · 51% VRAM
S
InternVL3 1B0.94B
OTHER·32K CTX· CHAT· VISION
82
TOK/S · 53% VRAM
S
MiniCPM5 1B1.08B
MINICPM·128K CTX· CHAT· REASONING· MULTILINGUAL
71
TOK/S · 57% VRAM
S
TinyLlama 1.1B1.1B
LLAMA·2K CTX· CHAT
70
TOK/S · 58% VRAM
S
LFM2.5-1.2B-Thinking1.2B
LFM·122K CTX· CHAT· REASONING· TOOL_USE
64
TOK/S · 61% VRAM
S
Llama-3.2-1B1.2B
LLAMA·4K CTX· CHAT
64
TOK/S · 61% VRAM
S
LFM2 1.2B1.2B
LFM·125K CTX· CHAT· TOOL_USE· MULTILINGUAL
64
TOK/S · 61% VRAM
S
Zamba2 1.2B1.2B
OTHER·4K CTX· CHAT
64
TOK/S · 61% VRAM
A
EXAONE-4.0-1.2B1.3B
EXAONE·64K CTX· CHAT
59
TOK/S · 64% VRAM
A
OPT 1.3B1.3B
OPT·2K CTX· CHAT
59
TOK/S · 64% VRAM
A
MiniCPM-V 4.61.3B
OTHER·256K CTX· CHAT· VISION
59
TOK/S · 64% VRAM
A
DeepSeek Coder 1.3B1.35B
DEEPSEEK·16K CTX· CODING
57
TOK/S · 66% VRAM
A
Phi-1 1.3B1.42B
PHI·2K CTX· CODING
54
TOK/S · 68% VRAM
A
Phi-1.5 1.3B1.42B
PHI·2K CTX· CHAT· CODING
54
TOK/S · 68% VRAM
A
Qwen2.5-Coder-1.5B1.5B
QWEN·32K CTX· CHAT· TOOL_USE· CODING
51
TOK/S · 70% VRAM
▸ NEXT STEP

Get personalized recommendations.

See ranked models with benchmark scores, run commands, and precise speed estimates for your GeForce MX550.

WHAT THIS CARD IS WORTH

MX550 holds 47 of the models in our catalogue and is, in practice, a Q4_K_M card — the largest it takes is Moondream2 1.9B 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
Moondream2 1.9B1.9B · Q4_K_M1.7 GB61 tok/sEST
Falcon3-1B1.67B · Q5_K_M1.8 GB60 tok/sEST
LFM2-VL 1.6B1.6B · Q5_K_M1.7 GB62 tok/sEST
Falcon-H1 1.5B1.55B · Q6_K1.7 GB56 tok/sEST
Qwen2.5-Coder-1.5B1.5B · Q6_K1.6 GB58 tok/sEST
Qwen2 Math 1.5B1.5B · Q6_K1.6 GB58 tok/sEST
Qwen 2.5 1.5B1.5B · Q6_K1.6 GB58 tok/sEST
Stella en 1.5B v51.5B · Q6_K1.6 GB58 tok/sEST
AGAINST CARDS OF SIMILAR MEMORY
M2 (8GB)5 GB$5992.8 tok/s per $100
M3 (8GB)5 GB$5992.8 tok/s per $100
M1 (8GB)5 GB$4992.2 tok/s per $100
RTX 2060 6GB6 GB$15026.7 tok/s per $100
MX5502 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

NVIDIA GeForce MX550 — 2 GB VRAM.

GEFORCE MX550 SPEC
BRAND
NVIDIA
VRAM
2 GB GDDR6
BANDWIDTH
96 GB/s
FP16 COMPUTE
2.7 TFLOPS
FP32 COMPUTE
2.7 TFLOPS
CUDA CORES
1,024
TDP
25 W
ARCHITECTURE
Turing
▸ AI CAPABILITY
47/ 449 models @ Q4

With 2 GB VRAM and 96 GB/s bandwidth, this GPU handles models up to 1.61B parameters.

Speed ≈ bandwidth / model_size × efficiency. A 7B model at Q4 runs at ~11 tok/s.

§ 01TOP MODELS FOR GEFORCE MX550
47 FIT · SHOWING 20
MODELSIZEVRAM Q4TOK/SAVG
GPT-2 XL 1.5B1.61B1.5 GB485.1
stablelm-2-1_6b1.6B1.5 GB489.5
Falcon-H1 1.5B1.55B1.4 GB5043.8
Qwen2.5-Coder-1.5B1.5B1.4 GB5119.6
Qwen2 Math 1.5B1.5B1.4 GB5119.6
Qwen 2.5 1.5B1.5B1.4 GB5130.2
Yi Coder 1.5B1.5B1.4 GB5114.6
Stella en 1.5B v51.5B1.4 GB51
Phi-1 1.3B1.42B1.4 GB547.2
Phi-1.5 1.3B1.42B1.4 GB547.2
DeepSeek Coder 1.3B1.35B1.3 GB5716.8
EXAONE-4.0-1.2B1.3B1.3 GB5918.9
OPT 1.3B1.3B1.3 GB595.3
MiniCPM-V 4.61.3B1.3 GB5921.5
LFM2.5-1.2B-Thinking1.2B1.2 GB6419.6
Llama-3.2-1B1.2B1.2 GB6410.1
LFM2 1.2B1.2B1.2 GB6415.6
Zamba2 1.2B1.2B1.2 GB6441.5
TinyLlama 1.1B1.1B1.2 GB7013.6
MiniCPM5 1B1.08B1.1 GB7126.5