Free AI has never been this good. The top free tiers now cover most everyday tasks — writing, research, coding, and Q&A — without a credit card. These picks balance what you actually get on the free plan, not just what's theoretically possible.
Last verified:
/Rankings refresh daily when model data changes
Rankings refresh dailyScored on 6 criteriaNo paid rankings
Your prompts routinely exceed 100K tokens, where the price quintuples, or the task needs sustained reasoning that Sonnet 5.5 handles far better.
Strengths
$0.10/$0.50 per 1M — half of GPT-5.6 Luna's $0.20/$1.20
Flex tier at $0.05/$0.25 for batch-style work
Reasoning effort can be turned off entirely for the cheapest calls
Weaknesses
Artificial Analysis scores it 38 on its Intelligence Index, behind Claude Haiku 5.5 (43) and Gemini 3.8 Flash (41)
Prompts above 272K input tokens are billed at a higher rate
Ranked alternatives
Strong backups depending on your budget, workload, and preferred tradeoffs.
AnthropicBudget
Claude Haiku 5.5
Anthropic's October 7, 2026 low-cost model and the first Haiku with adjustable reasoning effort — thinking can be switched off for simple requests or raised to max, at $0.10/$0.50 per 1M under 100K input tokens.
Verdict
Anthropic's budget model, now with adjustable reasoning, at $0.10/$0.50.
Quality score
82%
Pricing
$0.10/1M in
$0.50/1M out
Speed
Very fast
5/5 speed
Context
1M tokens
Announced September 28, 2026 alongside Sonnet 5.5; generally available October 7, 2026. Gateway id anthropic/claude-haiku-5.5. Tiered pricing: $0.10/$0.50 per 1M up to 100K input tokens, $0.50/$2.50 above. 1,000,000 context, 128,000 max output. Launch figures as reported by Anthropic: Terminal-Bench 4.0 39.2 (max effort), 31.6 (extra), 12.8 (low); OSWorld 2.1 offline subset 72.4 (Haiku 4.5: 15.7). Verified October 10, 2026.
BudgetFastHigh volumeSub-agentsNew
Best for
High-volume tool use, sub-agents and everyday tasks on a tight budget
Llama 3.2 1B Instruct is Meta's smallest production language model, designed for lightweight text tasks with an extremely low cost footprint. It excels at simple instruction-following, text classification, and on-device or edge deployment scenarios.
Verdict
The go-to model when cost per token matters more than output quality.
Quality score
25%
Pricing
$0.03/1M in
$0.20/1M out
Speed
Very fast
5/5 speed
Context
60k tokens
Output cost of ~$0.20/1M tokens is notably higher relative to input cost — factor this in for verbose generation tasks. Best suited for inference pipelines where outputs are short and structured. Available via multiple inference providers due to open-weight licensing.
Our pick for free AI. It scores 97/100 on the budget axis we weight this page by, and nothing else in this shortlist matches it on output quality.
OpenAI's September 22, 2026 low-cost reasoning model, replacing GPT-5.6 Luna at $0.10/$0.50 per 1M — half the predecessor's price, with the same 1.05M context.
Input
$0.10/1M
Output
$0.50/1M
Context
1.1M tokens
Speed
Very fast
What people actually use it for
Summarization, extraction and tagging at very high volume
Routine steps inside agent pipelines where a Sol-tier model would be overkill
Cheap first-pass coding help that a stronger model reviews
Where it wins
$0.10/$0.50 per 1M — half of GPT-5.6 Luna's $0.20/$1.20
Flex tier at $0.05/$0.25 for batch-style work
Reasoning effort can be turned off entirely for the cheapest calls
Where it falls down
Artificial Analysis scores it 38 on its Intelligence Index, behind Claude Haiku 5.5 (43) and Gemini 3.8 Flash (41)
Prompts above 272K input tokens are billed at a higher rate
Skip it if
You are choosing a budget model from scratch — Claude Haiku 5.5 costs the same and scores higher on Artificial Analysis's index.
Our verdict
A cheaper Luna rather than a smarter one. At $0.10/$0.50 it matches Claude Haiku 5.5 on price, but independent scoring puts Haiku 5.5 slightly ahead; choose Luna when you are already on the OpenAI stack.
Full pricing, benchmark table and release notes on the GPT-6 Luna page.
Here for latency: it answers fastest of anything listed for free AI, at 97/100 on budget.
Anthropic's October 7, 2026 low-cost model and the first Haiku with adjustable reasoning effort — thinking can be switched off for simple requests or raised to max, at $0.10/$0.50 per 1M under 100K input tokens.
Input
$0.10/1M
Output
$0.50/1M
Context
1M tokens
Speed
Very fast
What people actually use it for
Sub-agents in a larger agent system, where dozens of cheap calls replace one expensive one
Classification, extraction and routing at volume with thinking turned off
Light coding help — Anthropic reports 39.2% on Terminal-Bench 4.0 at max effort
Where it wins
$0.10/$0.50 per 1M below 100K input tokens — a twentieth of Sonnet 5.5
Effort is adjustable from none to max, so one model covers both cheap lookups and harder steps
Anthropic reports OSWorld 2.1 (offline subset) rising from 15.7% on Haiku 4.5 to 72.4%
Where it falls down
Long prompts cost five times more: above 100K input tokens the rate becomes $0.50/$2.50
Effort matters a great deal: Terminal-Bench 4.0 is 12.8% at low effort against 39.2% at max
Skip it if
Your prompts routinely exceed 100K tokens, where the price quintuples, or the task needs sustained reasoning that Sonnet 5.5 handles far better.
Our verdict
The cheapest way to put an Anthropic model in a high-volume pipeline. Keep requests under 100K tokens to stay on the low rate, and set effort per task — at low effort it is a fast classifier, at max it handles real tool-use work.
Pricing shifts, new alternatives, and recommendation changes — straight to your inbox.
No spam. Useful updates only. Affiliate disclosures always clearly labeled.
FAQ
What is the best AI for free AI?
For free AI, GPT-6 Luna (OpenAI) is our pick. OpenAI's budget tier at half the old price. It costs $0.1/1M input and $0.5/1M output tokens, with a 1.05M-token context window — enough headroom for all but the largest free AI jobs. Claude Haiku 5.5 is the closest alternative if it doesn't fit your setup.
Why GPT-6 Luna for free AI?
Because the work it is built for overlaps closely with free AI: summarization, extraction and tagging at very high volume and routine steps inside agent pipelines where a Sol-tier model would be overkill. A cheaper Luna rather than a smarter one. At $0.10/$0.50 it matches Claude Haiku 5.5 on price, but independent scoring puts Haiku 5.5 slightly ahead; choose Luna when you are already on the OpenAI stack.
What does it cost to use GPT-6 Luna for free AI?
On a moderate month — 10M input and 2M output tokens — GPT-6 Luna runs about $2.00 at list price, with no batch or caching discounts applied, so treat that as a ceiling. Llama 3.2 1B Instruct is the cheaper route at roughly $0.67 for the same volume, if free AI is high-volume enough for price to lead the decision.
When is GPT-6 Luna the wrong choice for free AI?
Artificial Analysis scores it 38 on its Intelligence Index, behind Claude Haiku 5.5 (43) and Gemini 3.8 Flash (41). Prompts above 272K input tokens are billed at a higher rate. Avoid it if you are choosing a budget model from scratch — Claude Haiku 5.5 costs the same and scores higher on Artificial Analysis's index. None of that rules it out for free AI on its own — but if one of those limits maps onto how you actually work, take the alternative on this page seriously rather than defaulting to the top pick.
Is there a cheaper AI that still handles free AI?
Llama 3.2 1B Instruct at $0.027/1M input is the budget option here. The go-to model when cost per token matters more than output quality. Expect a quality step down on the hardest cases — the usual pattern is to route routine free AI volume to Llama 3.2 1B Instruct and keep GPT-6 Luna for the work where a wrong answer is expensive.