OpenAI on NVIDIA Blackwell

Can I run gpt-oss 20B-A3.6B on an RTX 5070 Ti?

Yes. gpt-oss 20B-A3.6B at Q4_K_M uses 13.1 GB of the 14.2 GB available on a RTX 5070 Ti, and runs at about 185 tokens per second. You can push the context to 33K.

Fits, but tight

13.1 GB of 14.2 GB · 92%
014 GB
Weights 11.9 GB
KV cache 0.4 GB
Runtime overhead 0.8 GB

This fits with almost nothing to spare. A background application claiming VRAM will push it over. Drop to the next quantisation down, or quantise the KV cache to Q8_0 — that halves the cache for no meaningful quality loss.

Generation185tok/s
Prompt processing5133tok/s
Max context33Ktokens
KV per 1K tokens0GB

Every quantisation of gpt-oss 20B-A3.6B on a RTX 5070 Ti

Highlighted row is the highest quality that still fits at 8K context.

QuantisationbpwWeights TotalVerdictMax ctxtok/s
FP16 / BF16 16.00 38.9 GB 40.1 GB Won't fit 8.74
INT8 / W8A8 8.50 20.4 GB 21.6 GB Won't fit 26.0
FP8 (E4M3) 8.00 19.5 GB 20.6 GB Won't fit 29.7
Q6_K 6.56 16.0 GB 17.1 GB Won't fit 49.8
Q5_K_M 5.67 13.8 GB 15.0 GB Won't fit 93.5
Q5_K_S 5.52 13.4 GB 14.6 GB Won't fit 122
AWQ 4-bit 4.25 11.9 GB 13.1 GB Fits, but tight 32K 184
GPTQ 4-bit 4.25 11.9 GB 13.1 GB Fits, but tight 32K 184
MXFP4 4.25 11.9 GB 13.1 GB Fits, but tight 32K 184
Q4_K_M 4.85 11.9 GB 13.1 GB Fits, but tight 33K 185
Q4_K_S 4.58 11.3 GB 12.4 GB Runs comfortably 46K 192
Q4_0 4.55 11.2 GB 12.4 GB Runs comfortably 48K 193
IQ4_XS 4.25 10.5 GB 11.7 GB Runs comfortably 63K 202
Q3_K_M 3.91 9.7 GB 10.9 GB Runs comfortably 79K 214
IQ3_M 3.70 9.2 GB 10.4 GB Runs comfortably 89K 221
IQ3_XXS 3.06 7.8 GB 8.9 GB Runs comfortably 121K 249
Q2_K 2.63 6.8 GB 8.0 GB Runs comfortably 128K 272
IQ2_XXS 2.06 5.5 GB 6.7 GB Runs comfortably 128K 309
IQ1_M 1.75 4.8 GB 5.9 GB Runs comfortably 128K 333

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