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All estimates are approximations based on mathematical models and public specifications. Actual performance may vary. Do not make purchasing decisions based solely on these estimates.

Data sourced from Hugging Face, Ollama, and official model documentation. Model names and logos are trademarks of their respective owners.

© 2026 Will It Run AI — Fase Consulting Ibiza, S.L. (NIF: B57969656)

Home/Hardware/GPUs/GTX 1080 Ti 11GB
NVIDIA

NVIDIA

GTX 1080 Ti 11GB

GTX 10ConsumerPascalPCIe 3CUDA
11GB
VRAM
484GB/s
Bandwidth
22TFLOPS
FP16 Compute
88TOPS
INT8 Inference
VRAM11 GBBandwidth484 GB/sCompute22 TFInference88 TOPS
GTX 1080 Ti 11GBCategory AvgRTX A2000 12GB

Specifications

Compute
FP1622 TFLOPS
INT888 TOPS
ArchitecturePascal
Memory
VRAM11 GB
Bandwidth484 GB/s
General
FamilyGTX 10
SegmentConsumer
InterconnectPCIe 3
Compute PlatformCUDA

Architecture

Pascal

Pascal is NVIDIA's first 16nm FinFET GPU architecture, powering the GTX 10-series consumer cards and Tesla P100/P40 datacenter accelerators. It introduced unified memory architecture and NVLink interconnect for datacenter GPUs.

AI Relevance

No dedicated Tensor Cores — all AI inference runs on standard CUDA cores at FP16 or FP32 precision. Still usable for small models (7B Q4) on cards with sufficient VRAM like the GTX 1080 Ti (11 GB) or P40 (24 GB), but significantly slower than Turing and newer.

Process: TSMC 16nmPlatform: CUDAPrecisions: FP32, FP16

Recommendations by Workload

Agentic Coding

B

Codestral Mamba 7B

This model is still usable for agentic-coding, but it is not the most specialized pick. It sits in the middle of the current model mix. It fits natively with comfortable headroom. Known channels: huggingface, ollama.

Decode 66.9 tok/s · 42K ctx · llama.cpp
8.5 GB / 11.0 GB VRAM

Chat

C

Qwen 3 8B

This model is a direct match for chat. It belongs to a current frontier family for local AI. It fits natively with comfortable headroom. Known channels: huggingface, ollama, lm-studio.

Decode 58.5 tok/s · 11K ctx · llama.cpp
7.7 GB / 11.0 GB VRAM

Coding

C

Codestral Mamba 7B

This model is still usable for coding, but it is not the most specialized pick. It sits in the middle of the current model mix. It fits natively with comfortable headroom. Known channels: huggingface, ollama.

Decode 66.9 tok/s · 24K ctx · llama.cpp
7.4 GB / 11.0 GB VRAM

RAG

C

granite 8b code instruct 4k

This model is a direct match for rag. It sits in the middle of the current model mix. It should run, but memory headroom will be limited.

Decode 58.5 tok/s · 38K ctx · llama.cpp
9.4 GB / 11.0 GB VRAM

Reasoning

C

Qwen 3 8B

This model is a direct match for reasoning. It belongs to a current frontier family for local AI. It fits natively with comfortable headroom. Known channels: huggingface, ollama, lm-studio.

Decode 58.5 tok/s · 22K ctx · llama.cpp
8.1 GB / 11.0 GB VRAM

Full Model Compatibility

BartowskiBMeta Llama 3.1 8B Instruct
B56
8B8.1 GB59 tok/s22K ctx
dense
XtunerXllava llama 3 8b v1 1
B56
8B8.1 GB59 tok/s22K ctx
dense
UnslothDeepSeek R1 0528 Qwen3 8B
B56
8B8.1 GB59 tok/s22K ctx
dense
MaziyarPanahiMMeta Llama 3 8B Instruct
B56
8B8.1 GB59 tok/s22K ctx
dense
TheBlokeTLlama 2 7B Chat
B56
7B7.4 GB67 tok/s24K ctx
dense
TheBlokeTMistral 7B Instruct v0.2
B56
7B7.4 GB67 tok/s24K ctx
dense
MaziyarPanahiMMistral 7B Instruct v0.3
B56
7B7.4 GB67 tok/s24K ctx
dense
UnslothQwen3.5 9B
B55
9B8.9 GB52 tok/s20K ctx
dense
HauhauCSHQwen3.5 9B Uncensored HauhauCS Aggressive
B55
9B8.9 GB52 tok/s20K ctx
dense
Lmstudio-communityLQwen3.5 9B
B55
9B8.9 GB52 tok/s20K ctx
dense
UnslothQwen3.5 4B
C52
4B5.2 GB117 tok/s34K ctx
dense
Lmstudio-communityLgemma 3 4b it
C52
4B5.2 GB117 tok/s34K ctx
dense
BartowskiBLlama 3.2 3B Instruct
C52
3B5.0 GB135 tok/s35K ctx
dense
QwenQwen2.5 3B Instruct
C51
3B4.6 GB156 tok/s38K ctx
dense
BartowskiBgemma 2 2b it
C51
2B4.4 GB183 tok/s40K ctx
dense
Googlegemma 2b
C50
2B4.0 GB234 tok/s44K ctx
dense
TheDrummerTGemmasutra Mini 2B v1
C50
2B4.0 GB234 tok/s44K ctx
dense
QwenQwen2.5 1.5B Instruct
C49
1.5B3.7 GB286 tok/s47K ctx
dense
Hugging-quantsHLlama 3.2 1B Instruct Q8 0
C49
1B3.6 GB300 tok/s49K ctx
dense
TheBlokeTTinyLlama 1.1B Chat v1.0
C49
1.1B3.5 GB286 tok/s51K ctx
dense
Ggml-orgGSmolVLM 500M Instruct
C48
0.5B3.2 GB300 tok/s55K ctx
dense
Ggml-orgGembeddinggemma 300M
C48
0.3B3.0 GB300 tok/s58K ctx
dense
DeepSeekDeepSeek R1 671B
F0
671B417.1 GB2 tok/s4K ctx
moe
MistralDevstral 2 123B Instruct
F0
123B96.2 GB4 tok/s4K ctx
dense
Z.aiGLM-5
F0
744B462.1 GB2 tok/s4K ctx
moe
UnslothQwen3.5 27B
F0
27B22.7 GB17 tok/s8K ctx
dense
UnslothQwen3.5 35B A3B
F0
35B28.8 GB13 tok/s6K ctx
dense
Moonshot AIKimi K2.5
F0
1000B617.0 GB2 tok/s4K ctx
moe
MistralMistral Large 3
F0
675B420.2 GB2 tok/s4K ctx
+1moe
MistralMistral Small 4 119B
F0
119B75.6 GB11 tok/s4K ctx
moe
AlibabaQwen3-Coder 30B A3B Instruct
F0
30.5B21.4 GB40 tok/s8K ctx
moe
AlibabaQwen3-Coder 480B A35B Instruct
F0
480B300.3 GB3 tok/s4K ctx
moe
AlibabaQwen3-Coder-Next
F0
80B51.6 GB18 tok/s4K ctx
moe
UnslothQwen3.5 122B A10B
F0
122B80.8 GB4 tok/s4K ctx
dense
DeepSeekDeepSeek V3 671B
F0
671B417.1 GB2 tok/s4K ctx
moe
MistralMixtral 8x22B
F0
141B94.1 GB6 tok/s4K ctx
moe
AlibabaQwen 2.5 72B
F0
72B57.2 GB7 tok/s4K ctx
dense
AlibabaQwen 3 235B A22B
F0
235B148.8 GB5 tok/s4K ctx
moe
AlibabaQwen3-VL 30B A3B Instruct
F0
30B21.1 GB41 tok/s8K ctx
moe
UnslothQwen3.5 397B A17B
F0
397B306.2 GB2 tok/s4K ctx
dense
MistralDevstral Small 2 24B Instruct
F0
24B20.4 GB20 tok/s9K ctx
dense
MetaLlama 3.3 70B
F0
70B55.6 GB7 tok/s4K ctx
dense
MetaLlama 4 Maverick 17B 128E
F0
400B248.7 GB4 tok/s4K ctx
moe
CohereCommand A 111B
F0
111B87.1 GB4 tok/s4K ctx
dense
AlibabaQwen 2.5 Coder 32B
F0
32B26.5 GB15 tok/s7K ctx
dense
AlibabaQwen 2.5 VL 72B
F0
72B57.2 GB7 tok/s4K ctx
dense
Unslothgemma 3 27b it
F0
27B22.7 GB17 tok/s8K ctx
dense
Lmstudio-communityLQwen3.5 35B A3B
F0
35B28.8 GB13 tok/s6K ctx
dense
MistralCodestral 2 25.08
F0
22B18.9 GB21 tok/s9K ctx
dense
MistralDevstral Small 1.1
F0
24B20.4 GB20 tok/s9K ctx
dense

Just out of reach

Models you could run with an upgrade

High-quality models that need a bit more memory

DeepSeekDeepSeek R1 671B
671BTier 5Needs ~422.9 GB
MistralDevstral 2 123B Instruct
123BTier 5Needs ~115.5 GB
Runs on Mac Studio M3 Ultra 256GB
Z.aiGLM-5
744BTier 5Needs ~468.3 GB
UnslothQwen3.5 27B
27BTier 5Needs ~26.9 GB
Runs on RTX 5090 32GB (~$1,999)
UnslothQwen3.5 35B A3B
35BTier 5Needs ~34.3 GB
Runs on Mac mini M4 64GB (~$1,099)

Upgrade paths

Upgrade from GTX 1080 Ti 11GB

See what you unlock with more powerful hardware

Upgrade options

Upgrade options

NVIDIARTX A2000 12GBNext step up
12 GB VRAM (+1)
A
Unlocks LLaVA 1.6 13B, CodeLlama 13B Instruct, OLMo 2 13B+2 more

 

NVIDIARTX 3080 12GBNVIDIA upgrade
12 GB VRAM (+1)912 GB/s (+428)
A
Unlocks LLaVA 1.6 13B, CodeLlama 13B Instruct, OLMo 2 13B+2 more · +139% faster avg

~$799 MSRP

AMDRX 7600 XT 16GBBest value
16 GB VRAM (+5)
A
Unlocks StarCoder 15B, DeepSeek R1 Distill Qwen 14B, Phi-4-reasoning-plus 14B+28 more

~$329 MSRP

AMDAMD Instinct MI350X 288GBBiggest leap
288 GB VRAM (+277)8000 GB/s (+7516)
A
Unlocks Devstral 2 123B Instruct, Qwen3.5 27B, Qwen3.5 35B A3B+112 more · +1343% faster avg

~$8,000 MSRP

Compare this GPU