#1 pick
Anthropic's flagship tier: multi-step changes across large codebases and long-horizon agent work
Picks · by workload
Best OpenRouter Models
Not one universal winner — a practical list by workload. Use these picks for coding, long documents, high-volume extraction, multimodal work and agents.
Every pick here is a named, priced model on purpose. The line's newest codename, Union Alpha, is no longer the exception either: it was revealed as Unbiased Pareto on 18 September 2026 and delisted, so read what happened to its free window rather than planning around free capacity.
Best overall
Strong reasoning, tooling and production reliability.
#2 pick
$2 / $10 per million with a 1M-token window — the balanced tier most product teams land on
#3 pick
$2 / $10 per million — the same price as the GPT-6 Sol it replaces, with a 6.1 revision
#4 pick
Google's flagship tier at $2 / $10 per million — the same price as GPT-6.1 Sol and half of Claude Opus 5.5's
#5 pick
The model behind Union Alpha — the fourth codename in the anonymous line, revealed on 2026-09-18 and repriced since
Best for coding
Good code quality, debugging and technical explanation.
#1 pick
Anthropic's flagship tier: multi-step changes across large codebases and long-horizon agent work
#2 pick
$2 / $10 per million with a 1M-token window — the balanced tier most product teams land on
#3 pick
$2 / $10 per million — the same price as the GPT-6 Sol it replaces, with a 6.1 revision
#4 pick
Google's flagship tier at $2 / $10 per million — the same price as GPT-6.1 Sol and half of Claude Opus 5.5's
#5 pick
Open weights: meta-models/Muse-Spark-Open-816B-A42B on Hugging Face, so the checkpoint can leave Meta's API
Best for long context
Large context window for documents and transcripts.
#1 pick
1,048,576-token window with a 943,718-token output ceiling — the largest output allowance in this hub
#2 pick
Open weights: meta-models/Muse-Spark-Open-816B-A42B on Hugging Face, so the checkpoint can leave Meta's API
#3 pick
The widest input set here: text, image, video, file and audio all go in at $0.75 / $3.75 per million
#4 pick
Open weights (nvidia/NVIDIA-Nemotron-3.5-Super-VL): 12B active parameters out of 120B, and a 1M-token window
#5 pick
1M-token window at $0.68 / $2.09 per million — the cheapest 1M row here from a European vendor
Best for budget
Low input/output cost for high-volume workloads.
#1 pick
A 9B vision-language model with 2B active parameters, open weights on Hugging Face
#2 pick
Open weights (nvidia/NVIDIA-Nemotron-3.5-Super-VL): 12B active parameters out of 120B, and a 1M-token window
#3 pick
$0.10 in / $0.50 out per million — the cheapest row here from a frontier vendor
#4 pick
1,048,576-token window with a 943,718-token output ceiling at $0.0351 / $0.891 per million
#5 pick
Output is billed at $0: this row charges for input only, at $0.04 per million tokens
Best multimodal
Handles images, files, audio or video inputs.
#1 pick
Google's flagship tier at $2 / $10 per million — the same price as GPT-6.1 Sol and half of Claude Opus 5.5's
#2 pick
1,048,576-token window with a 943,718-token output ceiling — the largest output allowance in this hub
#3 pick
Open weights: meta-models/Muse-Spark-Open-816B-A42B on Hugging Face, so the checkpoint can leave Meta's API
#4 pick
A 9B vision-language model with 2B active parameters, open weights on Hugging Face
#5 pick
The widest input set here: text, image, video, file and audio all go in at $0.75 / $3.75 per million
Best for agents
Tool use, structured output and multi-step reasoning.
#1 pick
Anthropic's flagship tier: multi-step changes across large codebases and long-horizon agent work
#2 pick
$2 / $10 per million with a 1M-token window — the balanced tier most product teams land on
#3 pick
$2 / $10 per million — the same price as the GPT-6 Sol it replaces, with a 6.1 revision
#4 pick
Google's flagship tier at $2 / $10 per million — the same price as GPT-6.1 Sol and half of Claude Opus 5.5's
#5 pick
1,048,576-token window with a 943,718-token output ceiling — the largest output allowance in this hub