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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 A800 80GB
NVIDIA

NVIDIA

NVIDIA A800 80GB

Ampere DatacenterDatacenterAmpereSXMCUDA
80GB
VRAM
1.9kGB/s
Bandwidth
312TFLOPS
FP16 Compute
624TOPS
INT8 Inference
VRAM80 GBBandwidth1.9k GB/sCompute312 TFInference624 TOPS
NVIDIA A800 80GBCategory AvgMac Studio M1 Ultra 128GB

Specifications

Compute
FP16312 TFLOPS
INT8624 TOPS
ArchitectureAmpere
Memory
VRAM80 GB
Bandwidth1935 GB/s
General
FamilyAmpere Datacenter
SegmentDatacenter
InterconnectSXM
Compute PlatformCUDA

Architecture

Ampere

Ampere is NVIDIA's second-generation RTX architecture, built on Samsung's 8nm process. It introduced 3rd-generation Tensor Cores with support for sparsity-accelerated INT8 operations and improved FP16 throughput over Turing.

AI Relevance

Sparsity-aware Tensor Cores can effectively double throughput for structured sparse workloads. However, the lack of FP8 support means quantized inference is less efficient than Ada Lovelace or Blackwell.

Process: Samsung 8nmPlatform: CUDATensor Cores: Gen 3Precisions: FP32, FP16, BF16, INT8, INT4

Recommendations by Workload

Agentic Coding

B

Qwen3-Coder-Next

This model is still usable for agentic-coding, but it is not the most specialized pick. It belongs to a current frontier family for local AI. It fits natively with comfortable headroom. Known channels: huggingface, ollama, lm-studio.

Decode 93.7 tok/s · 44K ctx · llama.cpp
58.6 GB / 80.0 GB VRAM

Chat

C

Qwen 3 32B

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 77.3 tok/s · 21K ctx · llama.cpp
30.9 GB / 80.0 GB VRAM

Coding

B

Qwen3-Coder-Next

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

Decode 93.7 tok/s · 22K ctx · llama.cpp
58.5 GB / 80.0 GB VRAM

RAG

C

Command R 35B

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

Decode 70.7 tok/s · 62K ctx · llama.cpp
41.2 GB / 80.0 GB VRAM

Reasoning

B

Qwen3-Coder-Next

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 93.7 tok/s · 22K ctx · llama.cpp
58.5 GB / 80.0 GB VRAM

Full Model Compatibility

AlibabaQwen3-Coder-Next
B57
80B58.5 GB94 tok/s22K ctx
moe
MetaLlama 3.3 70B
C54
70B62.5 GB35 tok/s20K ctx
dense
AlibabaQwen 2.5 72B
C54
72B64.1 GB34 tok/s20K ctx
dense
AlibabaQwen 2.5 VL 72B
C54
72B64.1 GB34 tok/s20K ctx
dense
MistralMistral Small 4 119B
C53
119B82.5 GB60 tok/s16K ctx
moe
UnslothQwen3.5 35B A3B
C51
35B35.7 GB71 tok/s36K ctx
dense
Lmstudio-communityLQwen3.5 35B A3B
C51
35B35.7 GB71 tok/s36K ctx
dense
AlibabaQwen 2.5 Coder 32B
C51
32B33.4 GB77 tok/s38K ctx
dense
UnslothQwen3.5 27B
C50
27B29.6 GB92 tok/s43K ctx
dense
Unslothgemma 3 27b it
C50
27B29.6 GB92 tok/s43K ctx
dense
AlibabaQwen3-Coder 30B A3B Instruct
C50
30.5B28.3 GB210 tok/s45K ctx
moe
AlibabaQwen3-VL 30B A3B Instruct
C50
30B28.0 GB217 tok/s46K ctx
moe
MistralDevstral Small 2 24B Instruct
C49
24B27.3 GB103 tok/s47K ctx
dense
MistralDevstral Small 1.1
C49
24B27.3 GB103 tok/s47K ctx
dense
MistralCodestral 2 25.08
C49
22B25.8 GB113 tok/s50K ctx
dense
UnslothQwen3.5 9B
C46
9B15.8 GB275 tok/s81K ctx
dense
HauhauCSHQwen3.5 9B Uncensored HauhauCS Aggressive
C46
9B15.8 GB275 tok/s81K ctx
dense
Lmstudio-communityLQwen3.5 9B
C46
9B15.8 GB275 tok/s81K ctx
dense
BartowskiBMeta Llama 3.1 8B Instruct
C46
8B15.0 GB309 tok/s85K ctx
dense
XtunerXllava llama 3 8b v1 1
C46
8B15.0 GB309 tok/s85K ctx
dense
UnslothDeepSeek R1 0528 Qwen3 8B
C46
8B15.0 GB309 tok/s85K ctx
dense
MaziyarPanahiMMeta Llama 3 8B Instruct
C46
8B15.0 GB309 tok/s85K ctx
dense
TheBlokeTLlama 2 7B Chat
C46
7B14.3 GB354 tok/s90K ctx
dense
TheBlokeTMistral 7B Instruct v0.2
C46
7B14.3 GB354 tok/s90K ctx
dense
MaziyarPanahiMMistral 7B Instruct v0.3
C46
7B14.3 GB354 tok/s90K ctx
dense
UnslothQwen3.5 4B
C45
4B12.1 GB619 tok/s105K ctx
dense
BartowskiBLlama 3.2 3B Instruct
C45
3B11.9 GB713 tok/s108K ctx
dense
Lmstudio-communityLgemma 3 4b it
C45
4B12.1 GB619 tok/s105K ctx
dense
BartowskiBgemma 2 2b it
C45
2B11.3 GB966 tok/s113K ctx
dense
QwenQwen2.5 3B Instruct
C45
3B11.5 GB825 tok/s111K ctx
dense
Googlegemma 2b
C45
2B10.9 GB1237 tok/s117K ctx
dense
TheDrummerTGemmasutra Mini 2B v1
C45
2B10.9 GB1237 tok/s117K ctx
dense
QwenQwen2.5 1.5B Instruct
C45
1.5B10.6 GB1509 tok/s121K ctx
dense
Hugging-quantsHLlama 3.2 1B Instruct Q8 0
C45
1B10.5 GB1585 tok/s122K ctx
dense
TheBlokeTTinyLlama 1.1B Chat v1.0
C45
1.1B10.4 GB1509 tok/s123K ctx
dense
Ggml-orgGSmolVLM 500M Instruct
C45
0.5B10.1 GB1585 tok/s127K ctx
dense
Ggml-orgGembeddinggemma 300M
C45
0.3B9.9 GB1585 tok/s129K ctx
dense
UnslothQwen3.5 122B A10B
D40
122B87.7 GB22 tok/s15K ctx
dense
CohereCommand A 111B
D39
111B94.0 GB21 tok/s14K ctx
dense
DeepSeekDeepSeek R1 671B
F0
671B424.0 GB11 tok/s4K ctx
moe
MistralDevstral 2 123B Instruct
F0
123B103.1 GB20 tok/s12K ctx
dense
Z.aiGLM-5
F0
744B469.0 GB10 tok/s4K ctx
moe
Moonshot AIKimi K2.5
F0
1000B623.9 GB8 tok/s4K ctx
moe
MistralMistral Large 3
F0
675B427.1 GB11 tok/s4K ctx
+1moe
AlibabaQwen3-Coder 480B A35B Instruct
F0
480B307.2 GB14 tok/s4K ctx
moe
DeepSeekDeepSeek V3 671B
F0
671B424.0 GB11 tok/s4K ctx
moe
MistralMixtral 8x22B
F0
141B101.0 GB34 tok/s13K ctx
moe
AlibabaQwen 3 235B A22B
F0
235B155.7 GB28 tok/s8K ctx
moe
UnslothQwen3.5 397B A17B
F0
397B313.1 GB6 tok/s4K ctx
dense
MetaLlama 4 Maverick 17B 128E
F0
400B255.6 GB19 tok/s5K ctx
moe

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 ~429.8 GB
MistralDevstral 2 123B Instruct
123BTier 5Needs ~122.4 GB
Runs on Mac Studio M3 Ultra 256GB
Z.aiGLM-5
744BTier 5Needs ~475.2 GB
Moonshot AIKimi K2.5
1000BTier 5Needs ~628.9 GB
MistralMistral Large 3
675BTier 5Needs ~433.5 GB

Upgrade paths

Upgrade from NVIDIA A800 80GB

See what you unlock with more powerful hardware

Upgrade options

Upgrade options

AppleMac Studio M1 Ultra 128GBNext step up
128 GB Unified (+48)
B
Unlocks Solar Open 100B, Solar Open 100B i1

~$3,999 MSRP

NVIDIANVIDIA H20 96GBNVIDIA upgrade
96 GB VRAM (+16)4000 GB/s (+2065)
A
Unlocks Qwen3.5 122B A10B, Mixtral 8x22B, Command A 111B+3 more · +111% faster avg

 

AMDAMD Instinct MI325X 256GBBiggest leap
256 GB VRAM (+176)6000 GB/s (+4065)
A
Unlocks Devstral 2 123B Instruct, Qwen3.5 122B A10B, Mixtral 8x22B+12 more · +177% faster avg

 

AMDAMD Instinct MI350X 288GBBest value
288 GB VRAM (+208)8000 GB/s (+6065)
A
Unlocks Devstral 2 123B Instruct, Qwen3-Coder 480B A35B Instruct, Qwen3.5 122B A10B+13 more · +269% faster avg

~$8,000 MSRP

Compare this GPU