The cheapest AI model in this directory by API cost is Llama 4 Scout. The best cheap AI for most teams is still Gemini 3.1 Flash, because it gives better overall value.
The safest this comparison default, the cheaper option worth trying first, and the specialist pick — before you read the detail below.
Gemini 3.1 Flash is the strongest answer here for this comparison — pick it when quality of output matters more than the $0.50/1M/1M input you pay for it.
Llama 4 Maverick handles the same job for about 37% less per token. Start here and only move up if the output is not good enough.
Llama 4 Scout is the fastest of these for this comparison — worth it when latency is what the reader notices, not the last few points of reasoning depth.
Llama 4 Scout is the cheapest by list price in this dataset.
Gemini 3.1 Flash is the best cheap default for most people.
The lowest price is not the same thing as the best value.
Use the absolute cheapest model for internal, review-heavy, low-stakes tasks.
Use Gemini 3.1 Flash when the work still needs to be broadly useful.
Use task-specific cheap models when your volume is concentrated in one workflow, like coding or writing.
Switch the scoring lens to see whether the this comparison answer changes when cost, speed, or long-document depth leads the decision.
Google / Budget / Sep 2, 2026
Best cheap AI for broad day-to-day work — now with 1M context.
Ranks models by the broadest mix of coding, writing, research, and long-context usefulness.
You need premium reasoning depth or the highest coding benchmark scores.
Where the this comparison recommendation shifts once you weigh price or latency differently.
Best open-weight long-context option for self-hosted pipelines.
Best cheap AI for broad day-to-day work — now with 1M context.
Best flexible option for teams that need open-weight portability.
Best low-cost writing option for fast-moving content teams.
Best budget-focused coding specialist for high-volume developer teams.
List prices and published scores — the numbers this page's pick is built from.
| Model | Input | Output | Est. month | Context | Speed | Coding | Writing | Research |
|---|---|---|---|---|---|---|---|---|
| Gemini 3.1 FlashGoogle | $0.50/1M | $3.00/1M | $11 | 1M tokens | Very fast | 68 | 75 | 76 |
| Llama 4 ScoutMeta | $0.50/1M | $1.20/1M | $7.40 | 512k tokens | Fast | 54 | 60 | 78 |
| Llama 4 MaverickMeta | $0.60/1M | $1.60/1M | $9.20 | 256k tokens | Fast | 58 | 66 | 64 |
| Claude 4 HaikuAnthropic | $0.80/1M | $4.00/1M | $16 | 200k tokens | Very fast | 52 | 85 | 62 |
Scores out of 100 — how we evaluate models. “Est. month” is 10M in / 2M out at list price: a ceiling, no discounts.
Why each one is on the shortlist for this comparison, what it is genuinely good at, and where we would steer you away from it.
The default answer for this comparison — 75/100 on the writing axis, and the model we would start with unless the price below rules it out.
Fast, low-cost model with a 1M token context window — the best budget default for teams running high prompt volumes.
You need premium reasoning depth or the highest coding benchmark scores.
The best all-around budget model for most teams. Faster than its predecessor, cheaper, and with a 1M context window that outclasses every other budget option.
Full pricing, benchmark table and release notes on the Gemini 3.1 Flash page.
The fastest model in this shortlist for this comparison. Pick it when turnaround is what your readers or users notice.
Long-window open-weight model that handles large document sets at a low price point.
You want a hosted solution — Gemini 3.1 Flash gives more context for roughly the same cost.
A compelling pick for self-hosted long-context pipelines — but Gemini 3.1 Flash now offers 1M context hosted at a similar price.
Full pricing, benchmark table and release notes on the Llama 4 Scout page.
The cost-conscious pick for this comparison, about 37% less per token than Gemini 3.1 Flash than the top choice while holding 66/100 on writing.
Best flexible option for teams that need open-weight portability. Full Llama 4 Maverick review →
Also worth a look for this comparison, at 85/100 on the writing axis.
Best low-cost writing option for fast-moving content teams. Full Claude 4 Haiku review →
UseRightAI recommendations are based on practical decision factors people actually feel in day-to-day use.
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Llama 4 Scout is the cheapest model in this directory by combined input and output cost.
Gemini 3.1 Flash is the best cheap general-purpose AI in this directory because it stays fast, useful, and affordable at scale.
Codestral 25.01 is the best cheap coding specialist in this directory when low-cost engineering throughput matters most.
Claude 4 Haiku is the best low-cost writing option in this directory for fast drafts, edits, and support-style content workflows.
No. If poor output causes rework or mistakes, a slightly more expensive model can be the cheaper operational decision.
Because providers quote input and output separately, and output almost always costs several times more. A model advertised at a very low input price can still produce a larger bill than a pricier rival if it is verbose, because your spend tracks the length of the responses rather than the length of the prompts. Compare both numbers against a realistic workload before deciding — a moderate month of 10M input and 2M output tokens is a useful common basis, and the figure it produces is the one worth ranking on.
Retries and rework, mostly. A weaker model that needs two attempts at the same task has doubled its real price, and it has also spent your time. Reasoning models add a subtler version: the hidden thinking tokens are billed as output on most providers, so a cheap-looking reasoning model can cost more per completed task than an expensive non-reasoning one. Judge cost per finished piece of work, not cost per million tokens.
A lot, because most tokens in a real workload are not hard problems. Classification, extraction, routine drafting, and intermediate agent steps make up the bulk of the volume and rarely need a frontier model. Routing those to a budget model and reserving a premium one for genuinely difficult calls typically cuts spend substantially without a quality drop anyone notices. It is more work to build than picking one model, and it is usually the single largest saving available.