Cost · Updated August 5, 2026 · 6 min read

Cheapest Inference 2026: 88 Models From $0.04 per 1M

The cheapest inference in 2026 starts at $0.04 per 1M tokens. We rank 88 models by live per-provider price and recheck weekly, so the number stays current.

The cheapest AI inference API in 2026 depends on the model you want to run, because the market has split: frontier models cost dollars per million output tokens on their makers' endpoints, while open-weight models are served by cents-per-token across a dozen competing hosts. The table below is the current cheapest verified endpoint per tier, from our weekly cost check across 88 models.

The cheapest inference right now, by tier

Per 1M output tokens, cheapest verified endpoint from our latest check:

TierModelFromWhere
TinyMistral Nemo4 centsDeepInfra
SmallLlama 3.1 8B5 centsDeepInfra, Novita
Midgpt-oss-20b14 centsDeepInfra
Largegpt-oss-120b17 centsDeepInfra
LargeLlama 4 Scout30 centsDeepInfra
Very largeLlama 3.3 70B32 centsOpenRouter
Flagship-class openDeepSeek-V389 centsDeepInfra
ReasoningDeepSeek-R12.15 dollarsDeepInfra

All prices are verified against our live rankings, which re-check 88 models across every known provider weekly. Treat that live table as the source of truth, since prices here can be weeks stale by the time you read this. For context, frontier flagships list at 10 to 30 dollars per 1M output tokens. If your workload does not need frontier reasoning, the cheapest inference API is effectively always an open-weight model on a discount host, at 1 to 3 percent of flagship cost. The full comparison lives in LLM API pricing in 2026.

Who actually wins on price

Six names keep appearing at the top of our tables:

  • DeepInfra: the most frequent cheapest-endpoint winner across LLMs and Whisper transcription. See DeepInfra pricing in 2026.
  • Novita: consistently within cents of the leader across a large open-model catalog. See Novita AI pricing in 2026.
  • OpenRouter: an aggregator rather than a host; sometimes routes below every direct provider, and its free routes are unbeatable for development. See OpenRouter free models.
  • Groq and Cerebras: rarely the absolute cheapest, but the fastest tokens per second, which matters when latency is the real cost. Groq used to run a $10K startup credit program, but it is no longer published; see what happened to the Groq startup program.
  • Together AI and Fireworks: mid-priced but production-grade, with wide model coverage. Together AI's startup credits are worth checking once you have an entity.

Cheapest by cost vs cheapest by benchmark

Cost per token and speed per second are different rankings, and the cheapest-ai-inference-benchmark question is really asking about the second one. In every third-party throughput benchmark we track, Groq and Cerebras post the fastest tokens-per-second by a wide margin, often several times a standard GPU-backed endpoint, but they are rarely the lowest price per token. DeepInfra and Novita win on raw cost but run on more conventional GPU serving, so latency is closer to average. The decision rule: if your bottleneck is a user waiting on a response, benchmark tokens-per-second before you pick a host; if your bottleneck is a monthly bill for offline or async work, optimize for the price table above and ignore speed entirely.

Price is not the whole bill

Three things make nominally cheap inference expensive:

  • Rate limits: a cheap host that throttles you into retries is not cheap. Check advertised limits at your tier before committing volume.
  • Quantization and quality drift: some discount hosts serve more aggressively quantized weights. For most product tasks it does not matter; for evals it can. Test one day of real traffic before switching.
  • Egress and hidden per-request fees: rare among the majors we track, but read the pricing page. Our tables normalize to the posted per-token price.

The practical playbook: develop on free keys, pick your model, then take the cheapest host for that exact model from the rankings. Switching hosts later is usually a one-line base URL change, so the cost of a wrong first pick is nearly zero.

Cut it further

Cheap inference stacks with everything else: batch discounts halve frontier bills, caching discounts repeated prefixes, and startup credits cover months of usage before you pay cash. The 80 percent playbook is in how to cut your OpenAI API bill, and most of it applies to any provider.

Bottom line

Cheapest inference in 2026: an open-weight model on DeepInfra, Novita, or OpenRouter, at 4 to 90 cents per 1M output tokens depending on size, versus 10 to 30 dollars for frontier flagships. Match the model to the task, take the cheapest verified host from the live rankings, and claim the credits in the catalog before spending real money.

Related reading: LLM API pricing comparison, the cheapest way to run LLMs, every free LLM API key.

Frequently asked questions

What are the cheapest AI models for inference in 2026?

Tiny and small open-weight models are the cheapest to run: Mistral Nemo at 4 cents and Llama 3.1 8B at 5 cents per 1M output tokens on DeepInfra, our latest verified check. Mid-size models like gpt-oss-20b run 14 cents, and even a flagship-class open model like DeepSeek-V3 stays under a dollar. Frontier closed models cost 10 to 30 dollars per 1M output tokens by comparison.

What is the cheapest AI inference API in 2026?

For open-weight models, DeepInfra, Novita, and OpenRouter keep winning our weekly checks: small models from 4 to 5 cents per 1M output tokens, 120B-class models around 17 cents, DeepSeek-V3 under a dollar. The cheapest frontier options are the vendors' own mini tiers at 2 to 5 dollars.

What does the cheapest AI inference API actually cost?

From 4 cents per 1M output tokens for tiny open-weight models up to roughly 2.15 dollars for open reasoning models like DeepSeek-R1, versus 10 to 30 dollars per 1M output tokens for frontier flagships. Exact cost depends entirely on the model, not just the host.

How do I benchmark cheapest AI inference for performance, not just price?

Check tokens-per-second, not just dollars-per-token. Groq and Cerebras post the fastest throughput in most third-party benchmarks, often several times a standard GPU-backed endpoint, but usually cost more per token than DeepInfra or Novita. Benchmark on your own workload before committing volume to either extreme.

Is cheap inference lower quality?

Same weights, usually the same outputs. The real differences are rate limits, occasional aggressive quantization, and less mature tooling. Run a day of real traffic through a cheap host before moving volume; most teams find no measurable quality drop for product workloads.

How big is the price spread for the same model?

Routinely 2x to 4x between hosts, and up to 7x on some models we track. The spread is the whole reason per-model price rankings exist: picking the right host is the easiest cost cut in AI.

Should I use an aggregator like OpenRouter or go direct?

Aggregators give one key, automatic failover, and sometimes the lowest price; direct hosts give tighter control and occasionally undercut them. Many teams prototype on an aggregator and go direct for their highest-volume model.

How often do these prices change?

Monthly at least. Our last weekly re-check corrected 36 prices across 88 model tables, some by 2x or more in either direction. Never hardcode a provider decision from a blog post, including this one; check the live table.

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