Models & Pricing

All prices are per million tokens.

All Types

All Types

Base

Reasoning

Hybrid

Vision

All Architectures

All Architectures

Dense

MoE

All Sizes

All Sizes

Compact

Small

Medium

Large

Model	Tinker ID	Type	Arch	Size	Context	Prefill	Sample	Train
Nemotron-3-Ultra-550B-A55BLimited-time 50% discount	nvidia/NVIDIA-Nemotron-3-Ultra-550B-A55B-BF16	Hybrid	MoE	Large	64K	$1.66	$4.15	$4.98
Nemotron-3-Ultra-550B-A55B (256K)Limited-time 50% discount	nvidia/NVIDIA-Nemotron-3-Ultra-550B-A55B-BF16:peft:262144	Hybrid	MoE	Large	256K	$3.32	$8.30	$9.96
Nemotron-3-Super-120B-A12BLimited-time 50% discount	nvidia/NVIDIA-Nemotron-3-Super-120B-A12B-BF16	Hybrid	MoE	Large	64K	$0.38	$0.96	$1.16
Nemotron-3-Super-120B-A12B (256K)Limited-time 50% discount	nvidia/NVIDIA-Nemotron-3-Super-120B-A12B-BF16:peft:262144	Hybrid	MoE	Large	256K	$0.76	$1.92	$2.32
Nemotron-3-Nano-30B-A3BLimited-time 50% discount	nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-BF16	Hybrid	MoE	Medium	64K	$0.13	$0.33	$0.40
Kimi-K2.6	moonshotai/Kimi-K2.6	Reasoning + Vision	MoE	Large	32K	$1.47	$3.66	$4.40
Kimi-K2.6 (128K)	moonshotai/Kimi-K2.6:peft:131072	Reasoning + Vision	MoE	Large	128K	$5.15	$12.81	$15.40
Kimi-K2.5Retiring July 12	moonshotai/Kimi-K2.5	Reasoning + Vision	MoE	Large	32K	$1.47	$3.66	$4.40
Kimi-K2.5 (128K)Retiring July 12	moonshotai/Kimi-K2.5:peft:131072	Reasoning + Vision	MoE	Large	128K	$5.15	$12.81	$15.40
Qwen3.6-35B-A3B	Qwen/Qwen3.6-35B-A3B	Hybrid + Vision	MoE	Medium	64K	$0.36	$0.89	$1.07
Qwen3.6-27B	Qwen/Qwen3.6-27B	Hybrid + Vision	Dense	Medium	64K	$1.24	$3.73	$3.73
Qwen3.5-397B-A17B	Qwen/Qwen3.5-397B-A17B	Hybrid + Vision	MoE	Large	64K	$2.00	$5.00	$6.00
Qwen3.5-397B-A17B (256K)	Qwen/Qwen3.5-397B-A17B:peft:262144	Hybrid + Vision	MoE	Large	256K	$4.00	$10.00	$12.00
Qwen3.5-35B-A3B-Base	Qwen/Qwen3.5-35B-A3B-Base	Base	MoE	Medium	64K	$0.36	$0.89	$1.07
Qwen3.5-9B	Qwen/Qwen3.5-9B	Hybrid + Vision	Dense	Small	64K	$0.44	$1.33	$1.33
Qwen3.5-9B-Base	Qwen/Qwen3.5-9B-Base	Base	Dense	Small	64K	$0.44	$1.33	$1.33
Qwen3.5-4B	Qwen/Qwen3.5-4B	Hybrid + Vision	Dense	Compact	64K	$0.22	$0.67	$0.67
Qwen3-8B	Qwen/Qwen3-8B	Hybrid	Dense	Small	32K	$0.13	$0.40	$0.40
GPT-OSS-120B	openai/gpt-oss-120b	Reasoning	MoE	Medium	32K	$0.18	$0.44	$0.52
GPT-OSS-120B (128K)	openai/gpt-oss-120b:peft:131072	Reasoning	MoE	Medium	128K	$0.63	$1.54	$1.82
GPT-OSS-20B	openai/gpt-oss-20b	Reasoning	MoE	Small	32K	$0.12	$0.30	$0.36
DeepSeek-V3.1	deepseek-ai/DeepSeek-V3.1	Hybrid	MoE	Large	32K	$1.13	$2.81	$3.38

Model Types

• Base: Raw pretrained models with no chat or instruction tuning. Best for post-training research or running the full post-training pipeline yourself.
• Reasoning: Always produce chain-of-thought before their answer. Highest intelligence, higher latency and token cost.
• Hybrid: Run in both thinking and non-thinking modes. They reason by default, but chain-of-thought can be disabled via a renderer or argument for faster, cheaper direct answers.
• Vision: Vision-language models that accept images alongside text. Shown as a + Vision suffix on the underlying type (for example, Hybrid + Vision).

Architecture is either Dense (all parameters active per token) or MoE (mixture-of-experts, only a subset of parameters active per token). MoE models are highlighted in amber.

Pricing Terms

• Prefill: Processing input/prompt tokens (forward pass only)
• Sample: Generating output tokens (forward pass + sampling)
• Train: Forward and backward pass for gradient computation
• Context: Maximum sequence length. Models with :peft: suffix support extended context at higher prices.
• Tinker ID: The exact string to pass to create_lora_training_client(base_model=...) or create_sampling_client(base_model=...)

MoE models are priced by active parameters, making them significantly more cost-effective than dense models of similar quality.

Choosing a Model

• Cost-effective: Use MoE models (highlighted in amber)
• Research/post-training: Use Base models
• Task-specific fine-tuning: Start with a Hybrid model
• Low latency: Use a Hybrid model with chain-of-thought disabled
• High intelligence: Use Reasoning or Hybrid models (chain-of-thought)
• Vision tasks: Use models with Vision in the type

Retired Models

These models have been retired and can no longer be used for training or inference, grouped by retirement date. See Model deprecations for the recommended replacement for each.

June 12, 2026

• Qwen: Qwen3-235B-A22B-Instruct-2507, Qwen3-VL-235B-A22B-Instruct, Qwen3.5-35B-A3B, Qwen3.5-27B, Qwen3-32B, Qwen3-30B-A3B, Qwen3-30B-A3B-Instruct-2507, Qwen3-VL-30B-A3B-Instruct, Qwen3-30B-A3B-Base, Qwen3-8B-Base, Qwen3-4B-Instruct-2507
• Llama: Llama-3.3-70B-Instruct, Llama-3.1-70B, Llama-3.1-8B, Llama-3.1-8B-Instruct, Llama-3.2-3B, Llama-3.2-1B
• DeepSeek: DeepSeek-V3.1-Base
• Kimi: Kimi-K2-Thinking