FitMyLLM
▸ NVIDIA· AMPERE

NVIDIA RTX A3000 Mobile

Running LLMs on the RTX A3000 Mobile — the long read: which models fit at which quantisation, and the settings worth changing. · Or what a budget buys

VRAM
6 GB
BUDGET
BANDWIDTH
264
GB/S
MODELS Q4
130/449
29%
7B Q4 SPEED
~30
FAST
▸ MODEL COVERAGE @ Q429% OF ALL
▸ ESTIMATED SPEED· BY MODEL SIZE @ Q4

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

3B
~70
TOK/S
7B
~30
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
6 GB
BANDWIDTH
264 GB/s
FP16 COMPUTE
10.1 TFLOPS
TDP
70W
MEMORY
GDDR6
ARCHITECTURE
Ampere
CUDA CORES
4,096
TENSOR CORES
128
PCIE
Gen 4 x16
130
FAST MODELS · >30 TOK/S
Real-time chat speed
130
USABLE · >10 TOK/S
Comfortable for all tasks
130
TOTAL COMPATIBLE
Fit in VRAM at Q4
▸ RENT IT IN THE CLOUD

Buying RTX A3000 Mobile 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· 130
S
Falcon-H1R Tiny 90M0.09B
FALCON·256K CTX· CHAT· REASONING
2347
TOK/S · 9% VRAM
›
S
SmolLM2 135M0.135B
SMOLLM·2K CTX· CHAT
1564
TOK/S · 10% VRAM
›
S
nomic-embed-text-v1.5 100M0.14B
EMBEDDING·8K CTX· CHAT
1509
TOK/S · 10% VRAM
›
S
GPT-2 124M0.14B
GPT2·1K CTX· CHAT
1509
TOK/S · 10% VRAM
›
S
SmolVLM 256M0.256B
SMOLLM·8K CTX· CHAT· VISION
825
TOK/S · 11% VRAM
›
S
Gemma 3 270M0.27B
GEMMA·32K CTX· CHAT
782
TOK/S · 11% VRAM
›
S
Snowflake Arctic Embed M v2.00.305B
EMBEDDING·8K CTX· EMBEDDING· MULTILINGUAL
692
TOK/S · 11% VRAM
›
S
bge-large-en-v1.5 335M0.335B
EMBEDDING·1K CTX· CHAT
630
TOK/S · 12% VRAM
›
S
mxbai-embed-large-v10.335B
EMBEDDING·1K CTX· EMBEDDING
630
TOK/S · 12% VRAM
›
S
Snowflake Arctic Embed L0.335B
EMBEDDING·1K CTX· EMBEDDING
630
TOK/S · 12% VRAM
›
S
LFM2 350M0.35B
LFM·125K CTX· CHAT· TOOL_USE
603
TOK/S · 12% VRAM
›
S
SmolLM2 360M0.36B
SMOLLM·8K CTX· CHAT
587
TOK/S · 12% VRAM
›
S
GPT-2 Medium 345M0.38B
GPT2·1K CTX· CHAT
556
TOK/S · 12% VRAM
›
S
Qwen 2.5 0.5B0.5B
QWEN·32K CTX· CHAT
422
TOK/S · 13% VRAM
›
S
SmolVLM 500M0.5B
SMOLLM·8K CTX· CHAT· VISION
422
TOK/S · 13% VRAM
›
S
Falcon-H1 0.5B0.52B
FALCON·128K CTX· CHAT
406
TOK/S · 13% VRAM
›
S
BGE-M30.568B
EMBEDDING·8K CTX· EMBEDDING
372
TOK/S · 14% VRAM
›
S
Snowflake Arctic Embed L v2.00.568B
EMBEDDING·8K CTX· EMBEDDING· MULTILINGUAL
372
TOK/S · 14% VRAM
›
S
Qwen3-Embedding 0.6B0.6B
EMBEDDING·32K CTX· EMBEDDING· MULTILINGUAL
352
TOK/S · 14% VRAM
›
S
Falcon-H1R Tiny 0.6B0.6B
FALCON·32K CTX· CHAT· REASONING
352
TOK/S · 14% VRAM
›
S
Falcon Perception 0.6B0.6B
FALCON·4K CTX· VISION
352
TOK/S · 14% VRAM
›
S
Qwen 1.5 0.5B0.62B
QWEN·32K CTX· CHAT
341
TOK/S · 14% VRAM
›
S
LFM2 700M0.74B
LFM·125K CTX· CHAT· TOOL_USE
285
TOK/S · 16% VRAM
›
S
Qwen3 0.6B0.75B
QWEN·32K CTX· CHAT· REASONING
282
TOK/S · 16% VRAM
›
S
GPT-2 Large 774M0.81B
GPT2·1K CTX· CHAT
261
TOK/S · 16% VRAM
›
S
Qwen 3.5 0.8B0.87B
QWEN·256K CTX· CHAT· CODING· MULTILINGUAL
243
TOK/S · 17% VRAM
›
S
InternVL3 1B0.94B
OTHER·32K CTX· CHAT· VISION
225
TOK/S · 18% VRAM
›
S
MiniCPM5 1B1.08B
MINICPM·128K CTX· CHAT· REASONING· MULTILINGUAL
196
TOK/S · 19% VRAM
›
S
TinyLlama 1.1B1.1B
LLAMA·2K CTX· CHAT
192
TOK/S · 19% VRAM
›
S
LFM2.5-1.2B-Thinking1.2B
LFM·122K CTX· CHAT· REASONING· TOOL_USE
176
TOK/S · 20% VRAM
›
S
Llama-3.2-1B1.2B
LLAMA·4K CTX· CHAT
176
TOK/S · 20% VRAM
›
S
LFM2 1.2B1.2B
LFM·125K CTX· CHAT· TOOL_USE· MULTILINGUAL
176
TOK/S · 20% VRAM
›
S
Zamba2 1.2B1.2B
OTHER·4K CTX· CHAT
176
TOK/S · 20% VRAM
›
S
EXAONE-4.0-1.2B1.3B
EXAONE·64K CTX· CHAT
162
TOK/S · 21% VRAM
›
S
OPT 1.3B1.3B
OPT·2K CTX· CHAT
162
TOK/S · 21% VRAM
›
S
MiniCPM-V 4.61.3B
OTHER·256K CTX· CHAT· VISION
162
TOK/S · 21% VRAM
›
S
DeepSeek Coder 1.3B1.35B
DEEPSEEK·16K CTX· CODING
156
TOK/S · 22% VRAM
›
S
Phi-1 1.3B1.42B
PHI·2K CTX· CODING
149
TOK/S · 23% VRAM
›
S
Phi-1.5 1.3B1.42B
PHI·2K CTX· CHAT· CODING
149
TOK/S · 23% VRAM
›
S
granite-4.0-h-tiny 6.9B6.9BMoE
GRANITE·128K CTX· CHAT
141
TOK/S · 78% VRAM
›
▸ NEXT STEP

Get personalized recommendations.

See ranked models with benchmark scores, run commands, and precise speed estimates for your RTX A3000 Mobile.

WHAT THIS CARD IS WORTH

RTX A3000 Mobile holds 130 of the models in our catalogue and is, in practice, a Q4_K_M card — the largest it takes is Falcon-H1 7B 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
Falcon-H1 7B7.59B · Q4_K_M5.4 GB32 tok/sEST
Falcon-H1R 7B7.59B · Q4_K_M5.4 GB32 tok/sEST
Falcon Mamba 7B7.27B · Q4_K_M5.0 GB33 tok/sEST
WizardLM 2 7B7B · Q4_K_M5.3 GB35 tok/sEST
StarCoder2 7B7B · Q4_K_M5.0 GB35 tok/sEST
Dolly v2 7B6.9B · Q4_K_M5.3 GB35 tok/sEST
granite-4.0-h-tiny 6.9B6.9B · Q4_K_M5.0 GB162 tok/sEST
ChatGLM2 6B6.24B · Q5_K_M5.1 GB33 tok/sEST
AGAINST CARDS OF SIMILAR MEMORY
RTX 3080 10GB10 GB$42917.7 tok/s per $100
Arc B57010 GB$2198.2 tok/s per $100
Radeon RX 670010 GB$29912.0 tok/s per $100
Radeon RX 6750 GRE 10 GB10 GB$22915.7 tok/s per $100
RTX A3000 Mobile6 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 RTX A3000 Mobile — 6 GB VRAM.

▸ RTX A3000 MOBILE SPEC
BRAND
NVIDIA
VRAM
6 GB GDDR6
BANDWIDTH
264 GB/s
FP16 COMPUTE
10.1 TFLOPS
FP32 COMPUTE
10.1 TFLOPS
CUDA CORES
4,096
TENSOR CORES
128
TDP
70 W
ARCHITECTURE
Ampere
▸ AI CAPABILITY
130/ 449 models @ Q4

With 6 GB VRAM and 264 GB/s bandwidth, this GPU handles models up to 7B parameters.

Speed ≈ bandwidth / model_size × efficiency. A 7B model at Q4 runs at ~30 tok/s.

RENT IT — LIVE PRICES
Checking what the clouds are charging…
§ 01TOP MODELS FOR RTX A3000 MOBILE
130 FIT · SHOWING 20
MODELSIZEVRAM Q4TOK/SAVG
Alpaca 7B7B4.8 GB3027.7
Baichuan2 7B7B4.8 GB3021.5
Vicuna 7B7B4.8 GB3022.0
MPT-7B7B4.8 GB307.8
Orca 2 7B7B4.8 GB3026.1
WizardLM 2 7B7B4.8 GB3026.1
StarCoder2 7B7B4.8 GB3017.0
WizardCoder Python 7B7B4.8 GB3053.7
WizardLM 7B7B4.8 GB3015.5
OLMo 3.1 RLZero 7B Code7B4.8 GB3021.8
OLMo 3.1 RLZero 7B Math7B4.8 GB3021.8
Dolly v2 7B6.9B4.7 GB317.0
granite-4.0-h-tiny 6.9B6.9B4.7 GB14149.2
Llama 2 7B6.74B4.6 GB3121.1
CodeLlama 7B6.74B4.6 GB3128.1
LLaMA 1 7B6.74B4.6 GB3130.8
DeepSeek Coder 6.7B6.7B4.6 GB3223.6
OPT 6.7B6.7B4.6 GB3218.5
ChatGLM2 6B6.24B4.3 GB3420.7
ChatGLM3 6B6.24B4.3 GB3442.7