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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/NVIDIA T4 16GB

NVIDIA

NVIDIA T4 16GB

Turing DatacenterDatacenterTuringPCIe 3CUDA

16GB

VRAM

320GB/s

Bandwidth

65TFLOPS

FP16 Compute

130TOPS

INT8 Inference

$2,200 MSRP

NVIDIA T4 16GBCategory AvgRTX 4000 Ada 20GB

Specifications

Compute

FP1665 TFLOPS

INT8130 TOPS

ArchitectureTuring

Memory

VRAM16 GB

Bandwidth320 GB/s

General

FamilyTuring Datacenter

SegmentDatacenter

InterconnectPCIe 3

Compute PlatformCUDA

MSRP$2,200

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

C

Yi Coder 9B

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, lm-studio.

Decode 37.9 tok/s · 47K ctx · llama.cpp

10.8 GB / 16.0 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 42.6 tok/s · 16K ctx · llama.cpp

8.2 GB / 16.0 GB VRAM

Coding

C

Gemma 3 12B

This model is a direct match for coding. It sits in the middle of the current model mix. It fits natively with comfortable headroom. Known channels: huggingface, ollama, lm-studio.

Decode 28.4 tok/s · 22K ctx · llama.cpp

11.7 GB / 16.0 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 fits natively with comfortable headroom.

Decode 42.6 tok/s · 52K ctx · llama.cpp

9.9 GB / 16.0 GB VRAM

Reasoning

C

Qwen 3 14B

This model is a direct match for reasoning. It belongs to a current frontier family for local AI. It should run, but memory headroom will be limited. Known channels: huggingface, ollama, lm-studio.

Decode 24.4 tok/s · 19K ctx · llama.cpp

13.2 GB / 16.0 GB VRAM

Full Model Compatibility

9B9.4 GB38 tok/s27K ctx

Qwen3.5 9B Uncensored HauhauCS Aggressive

9B9.4 GB38 tok/s27K ctx

9B9.4 GB38 tok/s27K ctx

Meta Llama 3.1 8B Instruct

8B8.6 GB43 tok/s30K ctx

llava llama 3 8b v1 1

8B8.6 GB43 tok/s30K ctx

DeepSeek R1 0528 Qwen3 8B

8B8.6 GB43 tok/s30K ctx

Meta Llama 3 8B Instruct

8B8.6 GB43 tok/s30K ctx

Llama 2 7B Chat

7B7.9 GB49 tok/s33K ctx

Mistral 7B Instruct v0.2

7B7.9 GB49 tok/s33K ctx

Mistral 7B Instruct v0.3

7B7.9 GB49 tok/s33K ctx

4B5.7 GB85 tok/s45K ctx

Llama 3.2 3B Instruct

3B5.5 GB98 tok/s47K ctx

4B5.7 GB85 tok/s45K ctx

Qwen2.5 3B Instruct

3B5.1 GB114 tok/s50K ctx

2B4.9 GB133 tok/s52K ctx

2B4.5 GB171 tok/s57K ctx

Gemmasutra Mini 2B v1

2B4.5 GB171 tok/s57K ctx

Qwen2.5 1.5B Instruct

1.5B4.2 GB208 tok/s61K ctx

Llama 3.2 1B Instruct Q8 0

1B4.1 GB218 tok/s62K ctx

TinyLlama 1.1B Chat v1.0

1.1B4.0 GB208 tok/s64K ctx

SmolVLM 500M Instruct

0.5B3.7 GB218 tok/s69K ctx

embeddinggemma 300M

0.3B3.5 GB218 tok/s72K ctx

DeepSeek R1 671B

671B417.6 GB2 tok/s4K ctx

Devstral 2 123B Instruct

123B96.7 GB3 tok/s4K ctx

744B462.6 GB2 tok/s4K ctx

27B23.2 GB13 tok/s11K ctx

Qwen3.5 35B A3B

35B29.3 GB10 tok/s9K ctx

1000B617.5 GB2 tok/s4K ctx

Mistral Large 3

675B420.7 GB2 tok/s4K ctx

Mistral Small 4 119B

119B76.1 GB8 tok/s4K ctx

Qwen3-Coder 30B A3B Instruct

30.5B21.9 GB29 tok/s12K ctx

Qwen3-Coder 480B A35B Instruct

480B300.8 GB2 tok/s4K ctx

Qwen3-Coder-Next

80B52.1 GB13 tok/s5K ctx

Qwen3.5 122B A10B

122B81.3 GB3 tok/s4K ctx

DeepSeek V3 671B

671B417.6 GB2 tok/s4K ctx

141B94.6 GB5 tok/s4K ctx

72B57.7 GB5 tok/s4K ctx

Qwen 3 235B A22B

235B149.3 GB4 tok/s4K ctx

Qwen3-VL 30B A3B Instruct

30B21.6 GB30 tok/s12K ctx

Qwen3.5 397B A17B

397B306.7 GB2 tok/s4K ctx

Devstral Small 2 24B Instruct

24B20.9 GB14 tok/s12K ctx

70B56.1 GB5 tok/s5K ctx

Llama 4 Maverick 17B 128E

400B249.2 GB3 tok/s4K ctx

111B87.6 GB3 tok/s4K ctx

Qwen 2.5 Coder 32B

32B27.0 GB11 tok/s9K ctx

Qwen 2.5 VL 72B

72B57.7 GB5 tok/s4K ctx

27B23.2 GB13 tok/s11K ctx

Qwen3.5 35B A3B

35B29.3 GB10 tok/s9K ctx

Codestral 2 25.08

22B19.4 GB16 tok/s13K ctx

Devstral Small 1.1

24B20.9 GB14 tok/s12K ctx

Just out of reach

Models you could run with an upgrade

High-quality models that need a bit more memory

DeepSeek R1 671B

671BTier 5Needs ~423.4 GB

Devstral 2 123B Instruct

123BTier 5Needs ~116.0 GB

Runs on Mac Studio M3 Ultra 256GB

744BTier 5Needs ~468.8 GB

27BTier 5Needs ~27.4 GB

Runs on RTX 5090 32GB (~$1,999)

Qwen3.5 35B A3B

35BTier 5Needs ~34.8 GB

Runs on Mac mini M4 64GB (~$1,099)

Upgrade paths

Upgrade from NVIDIA T4 16GB

See what you unlock with more powerful hardware

Upgrade options

Upgrade options

RTX 4000 Ada 20GBNext step up

20 GB VRAM (+4)360 GB/s (+40)

Unlocks Qwen3-Coder 30B A3B Instruct, Qwen3-VL 30B A3B Instruct, Codestral 2 25.08+15 more · +28% faster avg

NVIDIA A10 24GBNVIDIA upgrade

24 GB VRAM (+8)600 GB/s (+280)

Unlocks Qwen3.5 27B, Qwen3-Coder 30B A3B Instruct, Qwen3-VL 30B A3B Instruct+32 more · +102% faster avg

Mac mini M4 64GBBest value

64 GB Unified (+48)

Unlocks Qwen3.5 27B, Qwen3.5 35B A3B, Qwen3-Coder 30B A3B Instruct+51 more

~$1,099 MSRP

AMD Instinct MI350X 288GBBiggest leap

288 GB VRAM (+272)8000 GB/s (+7680)

Unlocks Devstral 2 123B Instruct, Qwen3.5 27B, Qwen3.5 35B A3B+81 more · +2079% faster avg

~$8,000 MSRP

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