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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/RTX 2080 Ti 11GB
NVIDIA

NVIDIA

RTX 2080 Ti 11GB

RTX 20ConsumerTuringPCIe 3CUDA
11GB
VRAM
616GB/s
Bandwidth
27TFLOPS
FP16 Compute
216TOPS
INT8 Inference
$999 MSRP
VRAM11 GBBandwidth616 GB/sCompute27 TFInference216 TOPSValue2.7 TF/$k
RTX 2080 Ti 11GBCategory AvgRTX A2000 12GB

Specifications

Compute
FP1627 TFLOPS
INT8216 TOPS
ArchitectureTuring
Memory
VRAM11 GB
Bandwidth616 GB/s
General
FamilyRTX 20
SegmentConsumer
InterconnectPCIe 3
Compute PlatformCUDA
MSRP$999

Architecture

Turing

Turing is NVIDIA's first-generation RTX architecture, introducing dedicated RT and Tensor Cores to consumer GPUs for the first time. Built on TSMC's 12nm FinFET process.

AI Relevance

The first consumer architecture with Tensor Cores, enabling meaningful acceleration for INT8 and FP16 inference. However, limited VRAM (typically 6-11 GB) restricts modern LLM model sizes.

Process: TSMC 12nmPlatform: CUDATensor Cores: Gen 2Precisions: FP32, FP16, INT8, INT4

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

Chat

B

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

Coding

B

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 93.8 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 82.0 tok/s · 38K ctx · llama.cpp
9.4 GB / 11.0 GB VRAM

Reasoning

B

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

Full Model Compatibility

BartowskiBMeta Llama 3.1 8B Instruct
B57
8B8.1 GB82 tok/s22K ctx
dense
XtunerXllava llama 3 8b v1 1
B57
8B8.1 GB82 tok/s22K ctx
dense
UnslothDeepSeek R1 0528 Qwen3 8B
B57
8B8.1 GB82 tok/s22K ctx
dense
MaziyarPanahiMMeta Llama 3 8B Instruct
B57
8B8.1 GB82 tok/s22K ctx
dense
TheBlokeTLlama 2 7B Chat
B57
7B7.4 GB94 tok/s24K ctx
dense
TheBlokeTMistral 7B Instruct v0.2
B57
7B7.4 GB94 tok/s24K ctx
dense
UnslothQwen3.5 9B
B57
9B8.9 GB73 tok/s20K ctx
dense
MaziyarPanahiMMistral 7B Instruct v0.3
B57
7B7.4 GB94 tok/s24K ctx
dense
HauhauCSHQwen3.5 9B Uncensored HauhauCS Aggressive
B56
9B8.9 GB73 tok/s20K ctx
dense
Lmstudio-communityLQwen3.5 9B
B56
9B8.9 GB73 tok/s20K ctx
dense
UnslothQwen3.5 4B
C52
4B5.2 GB164 tok/s34K ctx
dense
Lmstudio-communityLgemma 3 4b it
C52
4B5.2 GB164 tok/s34K ctx
dense
BartowskiBLlama 3.2 3B Instruct
C52
3B5.0 GB189 tok/s35K ctx
dense
QwenQwen2.5 3B Instruct
C51
3B4.6 GB219 tok/s38K ctx
dense
BartowskiBgemma 2 2b it
C51
2B4.4 GB256 tok/s40K ctx
dense
Googlegemma 2b
C50
2B4.0 GB328 tok/s44K ctx
dense
TheDrummerTGemmasutra Mini 2B v1
C50
2B4.0 GB328 tok/s44K ctx
dense
QwenQwen2.5 1.5B Instruct
C49
1.5B3.7 GB400 tok/s47K ctx
dense
Hugging-quantsHLlama 3.2 1B Instruct Q8 0
C49
1B3.6 GB420 tok/s49K ctx
dense
TheBlokeTTinyLlama 1.1B Chat v1.0
C49
1.1B3.5 GB400 tok/s51K ctx
dense
Ggml-orgGSmolVLM 500M Instruct
C48
0.5B3.2 GB420 tok/s55K ctx
dense
Ggml-orgGembeddinggemma 300M
C48
0.3B3.0 GB420 tok/s58K ctx
dense
DeepSeekDeepSeek R1 671B
F0
671B417.1 GB3 tok/s4K ctx
moe
MistralDevstral 2 123B Instruct
F0
123B96.2 GB5 tok/s4K ctx
dense
Z.aiGLM-5
F0
744B462.1 GB3 tok/s4K ctx
moe
UnslothQwen3.5 27B
F0
27B22.7 GB24 tok/s8K ctx
dense
UnslothQwen3.5 35B A3B
F0
35B28.8 GB19 tok/s6K ctx
dense
Moonshot AIKimi K2.5
F0
1000B617.0 GB2 tok/s4K ctx
moe
MistralMistral Large 3
F0
675B420.2 GB3 tok/s4K ctx
+1moe
MistralMistral Small 4 119B
F0
119B75.6 GB16 tok/s4K ctx
moe
AlibabaQwen3-Coder 30B A3B Instruct
F0
30.5B21.4 GB56 tok/s8K ctx
moe
AlibabaQwen3-Coder 480B A35B Instruct
F0
480B300.3 GB4 tok/s4K ctx
moe
AlibabaQwen3-Coder-Next
F0
80B51.6 GB25 tok/s4K ctx
moe
UnslothQwen3.5 122B A10B
F0
122B80.8 GB6 tok/s4K ctx
dense
DeepSeekDeepSeek V3 671B
F0
671B417.1 GB3 tok/s4K ctx
moe
MistralMixtral 8x22B
F0
141B94.1 GB9 tok/s4K ctx
moe
AlibabaQwen 2.5 72B
F0
72B57.2 GB9 tok/s4K ctx
dense
AlibabaQwen 3 235B A22B
F0
235B148.8 GB8 tok/s4K ctx
moe
AlibabaQwen3-VL 30B A3B Instruct
F0
30B21.1 GB58 tok/s8K ctx
moe
UnslothQwen3.5 397B A17B
F0
397B306.2 GB2 tok/s4K ctx
dense
MistralDevstral Small 2 24B Instruct
F0
24B20.4 GB27 tok/s9K ctx
dense
MetaLlama 3.3 70B
F0
70B55.6 GB9 tok/s4K ctx
dense
MetaLlama 4 Maverick 17B 128E
F0
400B248.7 GB5 tok/s4K ctx
moe
CohereCommand A 111B
F0
111B87.1 GB6 tok/s4K ctx
dense
AlibabaQwen 2.5 Coder 32B
F0
32B26.5 GB21 tok/s7K ctx
dense
AlibabaQwen 2.5 VL 72B
F0
72B57.2 GB9 tok/s4K ctx
dense
Unslothgemma 3 27b it
F0
27B22.7 GB24 tok/s8K ctx
dense
Lmstudio-communityLQwen3.5 35B A3B
F0
35B28.8 GB19 tok/s6K ctx
dense
MistralCodestral 2 25.08
F0
22B18.9 GB30 tok/s9K ctx
dense
MistralDevstral Small 1.1
F0
24B20.4 GB27 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 RTX 2080 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 (+296)
A
Unlocks LLaVA 1.6 13B, CodeLlama 13B Instruct, OLMo 2 13B+2 more · +70% 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 (+7384)
A
Unlocks Devstral 2 123B Instruct, Qwen3.5 27B, Qwen3.5 35B A3B+112 more · +929% faster avg

~$8,000 MSRP

Compare this GPU