Venice

Models served by Venice

Model	Context	Input /M	Output /M	Cache read /M	Cache hit	Latency	Throughput
DeepSeek V3.2 deepseek/deepseek-v3.2:venice	163k	$0.35/M	$0.50/M	$0.17/M	N/A	1.8s	11 tps
DeepSeek V3.2 (Thinking) deepseek/deepseek-v3.2:thinking:venice	163k	$0.35/M	$0.50/M	$0.17/M	N/A	1.8s	11 tps
DeepSeek V4 Flash deepseek/deepseek-v4-flash:venice	1.0M	$0.14/M	$0.29/M	$0.03/M	0%	1.1s	33 tps
DeepSeek V4 Flash (Thinking) deepseek/deepseek-v4-flash:thinking:venice	1.0M	$0.14/M	$0.29/M	$0.03/M	0%	1.1s	33 tps
DeepSeek V4 Flash 0731 deepseek/deepseek-v4-flash-0731:venice	1M	$0.18/M	$0.37/M	$0.04/M	N/A	1s	43 tps
DeepSeek V4 Flash 0731 (Thinking) deepseek/deepseek-v4-flash-0731:thinking:venice	1M	$0.18/M	$0.37/M	$0.04/M	0%	1s	43 tps
DeepSeek V4 Pro deepseek/deepseek-v4-pro:venice	1.0M	$1.73/M	$3.47/M	$0.35/M	N/A	1.6s	48 tps
DeepSeek V4 Pro (Thinking) deepseek/deepseek-v4-pro:thinking:venice	1.0M	$1.73/M	$3.47/M	$0.35/M	N/A	1.6s	48 tps
GLM 5.1 FP8 z-ai/glm-5.1:venice	200k	$1.62/M	$5.08/M	$0.30/M	N/A	7.3s	11 tps
GLM 5.1 (Thinking) FP8 z-ai/glm-5.1:thinking:venice	200k	$1.62/M	$5.08/M	$0.30/M	N/A	7.3s	11 tps
GLM 5.2 FP8 z-ai/glm-5.2:venice	1.0M	$1.47/M	$4.62/M	$0.27/M	N/A	1.3s	83 tps
GLM 5.2 (Thinking) FP8 z-ai/glm-5.2:thinking:venice	1.0M	$1.47/M	$4.62/M	$0.27/M	48.7%	1.3s	83 tps
GLM 5.3 z-ai/glm-5.3:venice	1M	$1.84/M	$5.77/M	$0.34/M	N/A	2.3s	48 tps
GLM 5.3 (Thinking) z-ai/glm-5.3:thinking:venice	1M	$1.84/M	$5.77/M	$0.34/M	N/A	2.3s	48 tps
GLM 5.3 Flash z-ai/glm-5.3-flash:venice	1.0M	$0.16/M	$0.53/M	$0.03/M	0%	3s	45 tps
Kimi K2.7 Code INT4 moonshotai/kimi-k2.7-code:venice	262k	$0.79/M	$3.68/M	$0.17/M	N/A	45s	13 tps
MiniMax M3 FP8 minimax/minimax-m3:venice	512k	$0.31/M	$1.26/M	$0.06/M	N/A	1.1s	96 tps
MiniMax M3 Thinking FP8 minimax/minimax-m3:thinking:venice	512k	$0.31/M	$1.26/M	$0.06/M	32.7%	1.1s	96 tps
Qwen 3.6 35B A3B FP8 Qwen/Qwen3.6-35B-A3B:venice	262k	$0.10/M	$1.05/M	N/A	N/A	0.6s	60 tps
Qwen 3.6 35B A3B Thinking FP8 Qwen/Qwen3.6-35B-A3B:thinking:venice	262k	$0.10/M	$1.05/M	N/A	N/A	0.6s	60 tps
Qwen3 235B A22B FP8 qwen/qwen3-235b-a22b:venice	262k	$0.16/M	$0.79/M	N/A	N/A	0.7s	23 tps
Qwen3 235B A22B Thinking FP8 Qwen/Qwen3-235B-A22B-Thinking-2507:venice	256k	$0.47/M	$3.68/M	N/A	N/A	0.7s	109.5 tps
Qwen3.5 397B qwen/qwen3.5-397b-a17b:venice	258k	$0.79/M	$4.73/M	N/A	N/A	1s	73 tps
Qwen3.5 397B Thinking qwen/qwen3.5-397b-a17b-thinking:venice	258k	$0.79/M	$4.73/M	N/A	N/A	1s	73 tps
Qwen3.8 27B FP8 qwen3.8-27b:venice	262k	$0.47/M	$3.36/M	N/A	N/A	0.9s	30 tps
Qwen3.8 27B Thinking FP8 qwen3.8-27b:thinking:venice	262k	$0.47/M	$3.36/M	N/A	N/A	0.9s	30 tps
Qwen3.8 Max qwen3.8-max:venice	262k	$2.63/M	$7.88/M	$0.33/M	0%	6.1s	84 tps
Qwen3.8 Max Thinking qwen3.8-max:thinking:venice	262k	$2.63/M	$7.88/M	$0.33/M	0%	6.1s	84 tps

Prices are per million tokens and include the 5% provider-selection markup. Availability and pricing refresh continuously; each model page shows the live provider comparison.

Using Venice via the API

Append :venice to the model ID, set "provider": "venice" in the request body, or send an X-Provider: venice header. Explicit provider selection adds a 5% markup over that provider's base price; the prices in the table above already include it.

curl https://nano-gpt.com/api/v1/chat/completions \
  -H "Authorization: Bearer $NANOGPT_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "deepseek/deepseek-v3.2:venice",
    "messages": [{"role": "user", "content": "Hello"}]
  }'

See the API documentation for provider preferences, price-aware routing, and error behavior.