Frontier AI models: the top of each vendor's range and its cost

Frontier tier

Services found: 41

#	AI model	API $/1M (in / out)	Context window	Price / mo	Output $/1M	Overview
1	GPT-6 Astra OpenAI	$10 / $50	1.05M tokens	API only	50	View
2	Claude Opus 5 Anthropic	$5 / $25	1M tokens	API only	25	View
3	Claude Opus 4.8 Anthropic	$5 / $25	1M tokens	API only	25	View
4	Qwen3.8 Max (0902) Qwen	$2 / $6	1M tokens	API only	6	View
5	DeepSeek V4 Pro 0813 DeepSeek	$1.0494 / $3.1482	1.05M tokens	API only	3.148	View
6	DeepSeek V4 Pro 0423 DeepSeek	$0.95526 / $1.91052	1.05M tokens	API only	1.911	View
7	Qwen3.7 Max Qwen	$2.5 / $7.5	1M tokens	API only	7.5	View
8	MiniMax M3 MiniMax	$0.3 / $1.2	1.05M tokens	API only	1.2	View
9	MiMo-V2.5-Pro Xiaomi	$0.435 / $0.87	1.05M tokens	API only	0.87	View
10	Nemotron 3 Ultra NVIDIA	$0.625 / $3.125	262.1K tokens	API only	3.125	View
11	MiniMax M2.7 MiniMax	$0.3 / $1.2	204.8K tokens	API only	1.2	View
12	Trinity Large Thinking Arcee Ai	$0.25 / $0.8	262.1K tokens	API only	0.8	View
13	Mistral Large 3 2512 Mistral AI	$0.5 / $1.5	262.1K tokens	API only	1.5	View
14	Solar Pro 3 Upstage	$0.15 / $0.6	131.1K tokens	API only	0.6	View
15	Nano Banana Pro Google	$2 / $12		API only	12	View
16	DeepSeek V4 Pro DeepSeek		1M tokens	API only		View
17	Nova Premier Amazon			API only		View
18	Nova Pro Amazon		300K tokens	API only		View
19	Qwen3.8 Max Alibaba	$2 / $6	1M tokens	API only	6	View
20	Solar Pro 4 Upstage	$0.30 / $1.20	524.3K tokens	API only	1.2	View

Browse by need

Reasoning models169 models

Coding assistants17 models

Vision and images156 models

Long context 1M+82 models

Free tier available80 models

Open weights88 models

These 41 are the flagships - each vendor best available model, and the most expensive thing they sell. GPT-6 Astra, Claude Opus 5 and Claude Opus 4.8 sit at the top, with output from $0.60 to $50 per million tokens.

Frontier models earn their price where being wrong is costly and hard to detect: legal and financial analysis, architecture decisions, long agentic runs that compound their own errors. They are poor value for classification, routing or summarising short text. The disciplined pattern is a cheap model by default with escalation on confidence or complexity.

Best available, priciestThe ceiling of current capability, at the top of the price list.

Hard to detect errorsWorth paying where mistakes are subtle and expensive, not where they are obvious.

Escalation targetMost efficient as the second step, not the default.

Models with this capability

The 41 models below all support this capability. Prices are input and output per 1M tokens from the vendor official price list; for dirhams multiply by 3.6725. Tap a card to open the model page.

GPT-6 Astra

OpenAI

in $10out $501.05M tokens

Claude Opus 5

Anthropic

in $5out $251M tokens

Claude Opus 4.8

Anthropic

in $5out $251M tokens

in $1.0494out $3.14821.05M tokens

DeepSeek V4 Pro 0423

DeepSeek

in $0.95526out $1.910521.05M tokens

Qwen3.7 Max

Alibaba (Qwen)

in $2.5out $7.51M tokens

MiniMax M3

MiniMax

in $0.3out $1.21.05M tokens

How to choose

Define what triggers escalation: confidence, task type, or user tier.
Compare on your own hardest cases — benchmark gaps rarely match production gaps.
Use caching and batch aggressively; they apply here too and the savings are largest.
Track cost per resolved task, not cost per call.

Common mistakes

Frontier by defaultThe most common way to multiply an AI budget with no measurable gain.

Ignoring the mid tierSonnet 5 and GPT-5.6 Terra close most of the gap for a fifth of the price.

Who this suits

Legal and financeWhere a missed clause or condition carries real cost.

Agentic systemsLong runs where early errors compound.

Research and strategySynthesis across conflicting material.

Related filters

Low latency73 small, fast models for volume

Reasoning169 models that think before answering

Proprietary API151 closed-weight, API-only models

Priority tier65 models with a paid fast lane

All 239 modelsThe full rating with filters and prices

Frequently asked questions

When is the frontier tier worth it?

Where being wrong is costly and hard to detect: legal and financial analysis, architecture decisions, long agentic runs.

When is it a waste?

Classification, routing and summarising short text. A small model does these identically for a fifth of the price.

What is the sensible pattern?

A cheap model by default, escalating to the frontier on low confidence or high complexity.

Is the frontier tier worth it for coding?

For large cross-file refactors, yes. For routine code a dedicated coding model is cheaper and close.

How often does the frontier change?

Every major vendor shipped a new generation in 2026. Expect annual movement.

Ratings 1

Avg. score 5

Rate this page

Help us improve