Gemini 3.1 Flash-Lite vs GPT-6 Luna vs Claude Haiku 5.5: The Cheapest Quality AI APIs (October 2026)

As of October 23, 2026, the cheapest current models from OpenAI and Anthropic are GPT-6 Luna and Claude Haiku 5.5, both at $0.10 input and $0.50 output per million tokens (Haiku 5.5 for prompts up to 100K tokens), with Google's Gemini 3.1 Flash-Lite at $0.25 / $1.50. For high-volume classification, extraction, and short summaries, start with one of those three and escalate only the cases that fail.

This post replaces our March 15, 2026 review of Gemini 3.1 Flash-Lite, written when it set the price floor among major providers. Every price below is a list price from the vendor's own pricing page on October 23, 2026. We removed the March benchmark comparisons because we cannot re-verify them.

Quick answer: which budget model should you use?

• GPT-6 Luna: the lowest OpenAI price, with reasoning effort from none to max and a 1,050,000-token context.
• Claude Haiku 5.5: the same $0.10 / $0.50 for prompts up to 100K tokens; prices rise five times above that.
• Gemini 3.1 Flash-Lite: $0.25 / $1.50, still a solid choice on Google Cloud, with no shutdown before May 7, 2027.
• deepseek-flash: $0.15 / $0.60 off-peak (cache miss), with open weights under the MIT License.

Worked example: 50,000 support tickets a month

Assume each ticket sends about 800 input tokens and gets about 200 output tokens back, so a month is 40 million input and 10 million output tokens. Monthly cost is input millions times the input rate plus output millions times the output rate, with no caching or batch discount.

Second check, per ticket: on GPT-6 Luna, 800 input tokens cost $0.00008 and 200 output tokens cost $0.0001, so $0.00018 per ticket, and 50,000 tickets come to $9. On Gemini 3.1 Flash-Lite, the same ticket costs $0.0002 plus $0.0003, so $0.0005, and 50,000 tickets come to $25. The budget tier costs about a seventh of a mid-tier model for this job.

When cheap is good enough

A budget model is the right choice when three conditions hold: the task is simple (classification, extraction, short summaries, routing), the volume is high enough that per-token cost matters, and you have a check behind it, either a human review step or a stronger model for escalations.

• High-volume classification and tagging: sentiment, moderation queues, email categories, support ticket routing.
• First-pass summarization in retrieval pipelines, before a stronger model writes the final answer.
• Data extraction into structured output, such as names, dates, amounts, and addresses.
• Prototyping a pipeline before you know which model the final version needs.

When to pay for a stronger model

• Multi-step reasoning or decisions with real cost: use a balanced or top model such as GPT-6.1 Sol ($2 / $10), Claude Sonnet 5.5 ($2 / $10), Claude Opus 5.5 ($4 / $20), or Gemini 4 Argon ($2 / $10 through November 30, 2026, then $4 / $20).
• Production code that runs without thorough review.
• Long-form writing that must hold tone and follow detailed style rules.
• Single interactive questions, where the savings per query are too small to matter.

The two-tier pattern

1. Run the budget model on everything: classify, extract, summarize, or triage.
2. Have it flag low-confidence outputs, or score them with simple rules.
3. Send only the flagged items to a stronger model.
4. Measure the escalation rate for a week. Your savings depend on that rate, so do not assume it; measure it.

Verdict: which budget model to pick

• Choose GPT-6 Luna if you are on OpenAI and want reasoning control (none to max) at the lowest OpenAI list price.
• Choose Claude Haiku 5.5 if you are on Claude and your prompts stay under 100K tokens; it costs a tenth of legacy Haiku 4.5.
• Choose Gemini 3.1 Flash-Lite if you are on Google Cloud and want a model with a published earliest shutdown date (May 7, 2027).
• Choose deepseek-flash if you can schedule batch work off-peak and your data rules allow it; the weights are MIT-licensed if you would rather self-host.
• Choose Mistral Small 4 if you want Apache 2.0 open weights at $0.15 / $0.60 on the hosted API.

How to access Gemini 3.1 Flash-Lite

• Model ID in the Gemini API: gemini-3.1-flash-lite.
• Price: $0.25 input and $1.50 output per million tokens for text, image, and video input.
• Google's deprecations page lists its earliest shutdown as May 7, 2027.
• Google also offers Gemini 3.5 Flash-Lite ($0.30 / $2.50) and Gemini 3.8 Flash ($0.75 / $3.75 through December 31, 2026, then $1.50 / $7.50) if you need more capability within the Flash family.

FAQ

What is the cheapest AI API in 2026?

Among OpenAI, Anthropic, and Google, the lowest list prices on October 23, 2026 are GPT-6 Luna and Claude Haiku 5.5 at $0.10 input and $0.50 output per million tokens (Haiku 5.5 for prompts up to 100K). DeepSeek's deepseek-flash costs $0.15 / $0.60 off-peak on cache misses and $0.003 per million on off-peak cache hits.

Is Gemini 3.1 Flash-Lite still worth using?

Yes, if you are already on Google's stack. At $0.25 / $1.50 it costs more than GPT-6 Luna or Haiku 5.5 on list price, but Google lists no shutdown before May 7, 2027, and switching providers has its own cost. Re-run your evaluation set before you move a working pipeline.

Is Claude Haiku 5.5 cheaper than Haiku 4.5?

Yes, for prompts up to 100K tokens: $0.10 / $0.50 versus $1 / $5, a tenth of the price. Above 100K tokens Haiku 5.5 costs $0.50 / $2.50, still half of Haiku 4.5. Anthropic notes newer models use a tokenizer that produces about 30% more tokens for the same text, so measure your real token counts.

Are cheap models good enough for production?

For the right workloads, yes: classification, extraction, routing, and short summaries with a check behind them. Build an escalation path for low-confidence cases and measure how often it triggers before you commit.