AI Takeaway
- Which provider has the lowest listed rate here? DeepInfra's Llama 3.1 8B Turbo is $0.02 per million input tokens and $0.04 per million output tokens. That rate applies to a small model, not every model in its catalog.
- Which option is best for several model families? DIT offers one API key and supported models from multiple developers. Its catalog lists GLM 5.3 Flash at $0.12 input and $0.40 output per million tokens; confirm the charge before using it.
- Which API should you try for coding? Test DIT's GLM 5.3 Flash, DeepSeek Flash, and suitable models on Groq or Together AI against your own coding tasks. A lower token rate does not guarantee a lower cost per accepted change.
- Is there a universal cheapest AI API provider? No. The model, output volume, cache use, processing tier, and required quality determine the bill.
Cheapest AI API Providers at a Glance
The examples below are published USD rates per one million input and output tokens, checked on October 8, 2026. They compare different models, so the table is a shortlist of provider options rather than an equal-quality ranking. Standard paid, synchronous rates are shown unless a row says otherwise. Confirm the current rate before buying capacity; DIT's live model catalog shows its available market rates.
| Provider | Example Model | Input / 1M | Output / 1M | Best Fit |
|---|---|---|---|---|
| DIT | GLM 5.3 Flash | $0.12 | $0.40 | One API for supported models and market routing |
| DeepInfra | Llama 3.1 8B Instruct Turbo | $0.02 | $0.04 | Lowest listed entry rate in this shortlist |
| Groq | GPT-OSS 20B | $0.075 | $0.30 | Fast responses on a supported open model |
| Together AI | Qwen3.8 Flash | $0.15 | $0.47 | Broad hosted model choice |
| Google Gemini API | Gemini 2.5 Flash-Lite | $0.10 | $0.40 | Low-cost multimodal and long-context tasks |
| DeepSeek API | DeepSeek V4.1 Flash, off-peak | $0.15 | $0.60 | Direct coding and reasoning API |
DeepSeek's listed peak rate for this model is $0.30 input and $1.20 output. DIT's catalog and model-detail page currently display different output rates for GLM 5.3 Flash; the table uses the catalog quote, so verify the charge before purchasing. Free tiers, batch prices, cached input, tools, and taxes are excluded from the table. The model examples also differ in capability: a tiny instruction model is not a direct substitute for a coding agent.
Six Affordable AI API Providers
DIT: Multi-Provider Access with Market Pricing
DIT is an AI token exchange for teams that want to call supported models through one API key and a compatible endpoint. It evaluates qualified supply routes using price, quality, and availability signals. That makes it useful when your application may switch models or providers as requirements change.
For a concrete price example, DIT's model catalog lists GLM 5.3 Flash at $0.12 input and $0.40 output per million tokens. Its model-detail page describes coding, tool use, and long-context work as intended applications, but currently shows a different output rate. This is a model-specific quote, not a promise that DIT is cheaper than every direct or hosted API. Check the charged rate, endpoint support, and route availability for the model you intend to use.
Best for: Applications that need several model families or want to test an alternative supply path without separate provider integrations. Watch for: The routing layer must meet your latency, feature, privacy, and reliability requirements. A model with only one eligible route cannot offer provider failover for that request.
How to Use DIT for a Lower-Cost API Stack:
- Create one DIT API key and choose a supported model that meets your task's quality requirements.
- Set the base URL of an OpenAI-compatible client to
https://api.dit.ai/v1and send a representative set of requests. - Compare the charged rate, response quality, latency, and completed tasks before moving more traffic.
DeepInfra: Very Low Rates for Small Open Models
DeepInfra's Llama 3.1 8B Instruct Turbo is listed at $0.02 input and $0.04 output per million tokens. That is the lowest paid token rate among the representative models in this article. Its OpenAI-compatible API also reduces integration work for teams already using that request format.
Best for: Classification, extraction, short answers, and other tasks where a small model passes your quality checks. Watch for: The low rate belongs to a specific 8B model. A complex coding task may need a different, more expensive model or several retries.
Groq: Fast Responses on Supported Models
Groq lists GPT-OSS 20B at $0.075 input and $0.30 output per million tokens, with a published speed of roughly 1,000 output tokens per second for that model. It is a useful candidate when an interactive feature needs a fast first response and the model's capabilities match the job.
Best for: Responsive assistants, simple code help, and high-volume tasks suited to Groq's current catalog. Watch for: Verify the exact model, rate limits, context window, and tool support. Fast generation alone does not make a response useful or a workload cheaper.
Together AI: Broad Hosted Model Choice
Together AI offers serverless inference across many open models, with dedicated capacity for teams that need it. Its current price list shows Qwen3.8 Flash at $0.15 input and $0.47 output per million tokens. A broad catalog helps you test whether a slightly more capable model reduces errors enough to justify a higher token price.
Best for: Teams evaluating several open models or moving from variable serverless traffic to dedicated throughput. Watch for: Pricing and capabilities differ by model and deployment type. Check that your selected endpoint supports the tools, context length, and output format your application needs.
Google Gemini API: Low-Cost Multimodal Work
Google lists Gemini 2.5 Flash-Lite at $0.10 input and $0.40 output per million tokens on its standard paid tier. It accepts text, image, and video input, and Google also lists free access subject to model-specific limits. Batch processing has a lower published rate when your job can wait.
Best for: High-volume lightweight tasks that combine text with other input types, or long-context experiments in Google's model family. Watch for: Free-tier quotas and the billing rules for audio, caching, storage, and grounding differ from ordinary text requests. Compare the billable units before treating a free or batch rate as your production price. The AI model pricing guide explains a practical way to do that.
DeepSeek API: Direct Access for Coding and Reasoning
DeepSeek's current Flash model is DeepSeek V4.1 Flash, called through the deepseek-flash model ID. Its published off-peak rates are $0.15 input and $0.60 output per million tokens; peak rates are twice as high. The API documentation lists tool calls, JSON output, a large context window, and both OpenAI and Anthropic request formats.
Best for: Teams that want a direct API for coding, tool-based agents, and reasoning tasks. Watch for: The cheapest schedule depends on when requests run and whether cached input qualifies for its separate rate. Use the current model ID rather than an older V4 Flash alias when configuring a new application.
Cheapest AI API for Coding: Which Provider Fits?
For routine code explanations, formatting, and narrow edits, start with a low-cost model and measure whether its output passes tests or review. Groq's GPT-OSS 20B, Together AI's Qwen3.8 Flash, and DIT's GLM 5.3 Flash are concrete candidates to test. DeepInfra's 8B example may be inexpensive enough for simple mechanical tasks, but its sticker price alone says little about performance on multi-file changes.
For debugging, tool loops, and repository-wide edits, compare DIT's coding-capable models with DeepSeek Flash and other models that support the required context and tools. Run the same tasks through each route. Record successful changes, retries, human fixes, input and output tokens, and latency. Choose by cost per accepted result, then reassess when the workload changes. DIT's routing strategy guide covers the price, quality, and availability signals behind that decision.
How to Choose the Cheapest LLM API Provider for Your Workload
Shortlist by the exact task first. A small, cheap model is a sound choice when it completes lightweight requests reliably. A direct provider makes sense when one model's native features are essential. A multi-provider service becomes more useful when you need to compare supported models or supply routes through one integration; DIT's gateway versus direct API guide lays out that operational trade-off.
Then estimate a bill from representative prompts: input tokens × input rate, plus output tokens × output rate, plus cached input, retries, and any additional charges. Divide total spend by successful outcomes. That calculation exposes when a low listed rate creates expensive failures. For more ways to reduce the bill after choosing a provider, see LLM API Cost Optimization.
The cheapest AI API provider is the one that meets your quality and operating requirements at the lowest measured cost. Keep the price table current, and rerun the comparison whenever the model, traffic mix, or provider terms change.
Use one DIT key to access supported models through a market of qualified AI providers.
Get your API key
