FitMyLLM
NVIDIA· PASCAL

NVIDIA GeForce GTX 1080

Running LLMs on the GeForce GTX 1080 — 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
320
GB/S
MODELS Q4
201/449
45%
7B Q4 SPEED
~37
FAST
▸ 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
~85
TOK/S
7B
~37
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
320 GB/s
FP16 COMPUTE
0.1 TFLOPS
TDP
180W
MEMORY
GDDR5X
ARCHITECTURE
Pascal
CUDA CORES
2,560
PCIE
Gen 3 x16
192
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 GeForce GTX 1080 (or anything bigger) without committing. Pay by the second, cancel anytime.

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▸ COMPATIBLE MODELS· 201
S
Falcon-H1R Tiny 90M0.09B
FALCON·256K CTX· CHAT· REASONING
2844
TOK/S · 7% VRAM
S
SmolLM2 135M0.135B
SMOLLM·2K CTX· CHAT
1896
TOK/S · 7% VRAM
S
nomic-embed-text-v1.5 100M0.14B
EMBEDDING·8K CTX· CHAT
1829
TOK/S · 7% VRAM
S
GPT-2 124M0.14B
GPT2·1K CTX· CHAT
1829
TOK/S · 7% VRAM
S
SmolVLM 256M0.256B
SMOLLM·8K CTX· CHAT· VISION
1000
TOK/S · 8% VRAM
S
Gemma 3 270M0.27B
GEMMA·32K CTX· CHAT
948
TOK/S · 8% VRAM
S
Snowflake Arctic Embed M v2.00.305B
EMBEDDING·8K CTX· EMBEDDING· MULTILINGUAL
839
TOK/S · 8% VRAM
S
bge-large-en-v1.5 335M0.335B
EMBEDDING·1K CTX· CHAT
764
TOK/S · 9% VRAM
S
mxbai-embed-large-v10.335B
EMBEDDING·1K CTX· EMBEDDING
764
TOK/S · 9% VRAM
S
Snowflake Arctic Embed L0.335B
EMBEDDING·1K CTX· EMBEDDING
764
TOK/S · 9% VRAM
S
LFM2 350M0.35B
LFM·125K CTX· CHAT· TOOL_USE
731
TOK/S · 9% VRAM
S
SmolLM2 360M0.36B
SMOLLM·8K CTX· CHAT
711
TOK/S · 9% VRAM
S
GPT-2 Medium 345M0.38B
GPT2·1K CTX· CHAT
674
TOK/S · 9% VRAM
S
Qwen 2.5 0.5B0.5B
QWEN·32K CTX· CHAT
512
TOK/S · 10% VRAM
S
SmolVLM 500M0.5B
SMOLLM·8K CTX· CHAT· VISION
512
TOK/S · 10% VRAM
S
Falcon-H1 0.5B0.52B
FALCON·128K CTX· CHAT
492
TOK/S · 10% VRAM
S
BGE-M30.568B
EMBEDDING·8K CTX· EMBEDDING
451
TOK/S · 10% VRAM
S
Snowflake Arctic Embed L v2.00.568B
EMBEDDING·8K CTX· EMBEDDING· MULTILINGUAL
451
TOK/S · 10% VRAM
S
Qwen3-Embedding 0.6B0.6B
EMBEDDING·32K CTX· EMBEDDING· MULTILINGUAL
427
TOK/S · 11% VRAM
S
Falcon-H1R Tiny 0.6B0.6B
FALCON·32K CTX· CHAT· REASONING
427
TOK/S · 11% VRAM
S
Falcon Perception 0.6B0.6B
FALCON·4K CTX· VISION
427
TOK/S · 11% VRAM
S
Qwen 1.5 0.5B0.62B
QWEN·32K CTX· CHAT
413
TOK/S · 11% VRAM
S
LFM2 700M0.74B
LFM·125K CTX· CHAT· TOOL_USE
346
TOK/S · 12% VRAM
S
Qwen3 0.6B0.75B
QWEN·32K CTX· CHAT· REASONING
341
TOK/S · 12% VRAM
S
GPT-2 Large 774M0.81B
GPT2·1K CTX· CHAT
316
TOK/S · 12% VRAM
S
Qwen 3.5 0.8B0.87B
QWEN·256K CTX· CHAT· CODING· MULTILINGUAL
294
TOK/S · 13% VRAM
S
InternVL3 1B0.94B
OTHER·32K CTX· CHAT· VISION
272
TOK/S · 13% VRAM
S
MiniCPM5 1B1.08B
MINICPM·128K CTX· CHAT· REASONING· MULTILINGUAL
237
TOK/S · 14% VRAM
S
TinyLlama 1.1B1.1B
LLAMA·2K CTX· CHAT
233
TOK/S · 15% VRAM
S
LFM2.5-1.2B-Thinking1.2B
LFM·122K CTX· CHAT· REASONING· TOOL_USE
213
TOK/S · 15% VRAM
S
Llama-3.2-1B1.2B
LLAMA·4K CTX· CHAT
213
TOK/S · 15% VRAM
S
LFM2 1.2B1.2B
LFM·125K CTX· CHAT· TOOL_USE· MULTILINGUAL
213
TOK/S · 15% VRAM
S
Zamba2 1.2B1.2B
OTHER·4K CTX· CHAT
213
TOK/S · 15% VRAM
S
EXAONE-4.0-1.2B1.3B
EXAONE·64K CTX· CHAT
197
TOK/S · 16% VRAM
S
OPT 1.3B1.3B
OPT·2K CTX· CHAT
197
TOK/S · 16% VRAM
S
MiniCPM-V 4.61.3B
OTHER·256K CTX· CHAT· VISION
197
TOK/S · 16% VRAM
S
DeepSeek Coder 1.3B1.35B
DEEPSEEK·16K CTX· CODING
190
TOK/S · 16% VRAM
S
Phi-1 1.3B1.42B
PHI·2K CTX· CODING
180
TOK/S · 17% VRAM
S
Phi-1.5 1.3B1.42B
PHI·2K CTX· CHAT· CODING
180
TOK/S · 17% VRAM
S
LFM2 8B A1B8.3BMoE
LFM·125K CTX· CHAT· TOOL_USE· MULTILINGUAL
171
TOK/S · 70% VRAM
▸ NEXT STEP

Get personalized recommendations.

See ranked models with benchmark scores, run commands, and precise speed estimates for your GeForce GTX 1080.

WHAT THIS CARD IS WORTH

GTX 1080 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 GB30 tok/sEST
Bamba 9B v29.78B · Q4_K_M7.2 GB29 tok/sEST
RecurrentGemma 9B9.63B · Q4_K_M6.8 GB29 tok/sEST
glm-4-9b9.4B · Q4_K_M6.6 GB30 tok/sEST
Yi 1.5 9B9B · Q4_K_M6.5 GB31 tok/sEST
Yi Coder 9B9B · Q4_K_M6.5 GB31 tok/sEST
Ministral 3 8B8.92B · Q4_K_M6.6 GB32 tok/sEST
Ministral 3 8B Reasoning8.92B · Q4_K_M6.6 GB32 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

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 GTX 1080 — 8 GB VRAM.

GEFORCE GTX 1080 SPEC
BRAND
NVIDIA
VRAM
8 GB GDDR5X
BANDWIDTH
320 GB/s
FP16 COMPUTE
0.1 TFLOPS
FP32 COMPUTE
8.9 TFLOPS
CUDA CORES
2,560
TDP
180 W
ARCHITECTURE
Pascal
▸ AI CAPABILITY
201/ 449 models @ Q4

With 8 GB VRAM and 320 GB/s bandwidth, this GPU handles models up to 9.63B parameters.

Speed ≈ bandwidth / model_size × efficiency. A 7B model at Q4 runs at ~37 tok/s.

RENT IT — LIVE PRICES
Checking what the clouds are charging…
§ 01TOP MODELS FOR GEFORCE GTX 1080
201 FIT · SHOWING 20
MODELSIZEVRAM Q4TOK/SAVG
RecurrentGemma 9B9.63B6.4 GB2735.0
glm-4-9b9.4B6.2 GB2720.5
gemma-2-9b9.2B6.1 GB2830.2
Yi 1.5 9B9B6.0 GB2830.3
Yi Coder 9B9B6.0 GB2835.8
Ministral 3 8B8.92B5.9 GB2925.7
Ministral 3 8B Reasoning8.92B5.9 GB29
NVIDIA-Nemotron-Nano-9B-v28.9B5.9 GB2944.2
InternLM3 8B Instruct8.8B5.9 GB2938.7
Gemma 1 7B8.54B5.7 GB3024.7
CodeGemma 7B8.54B5.7 GB3040.2
LFM2 8B A1B8.3B5.6 GB17124.3
Seed-Coder 8B Instruct8.25B5.5 GB3134.1
Seed-Coder 8B Reasoning8.25B5.5 GB3132.9
DeepSeek R1-0528 Qwen3 8B8.2B5.5 GB3136.3
Qwen3-8B8.2B5.5 GB3143.3
Granite 3.0 8B8.17B5.5 GB3136.4
Granite 3.1 8B8.17B5.5 GB3138.6
Command-R7B8.03B5.4 GB3235.3
Aya Expanse 8B8B5.4 GB3227.8