Data Analysis: The $0.025 Floor — Cheapest AI Coding Models Dropped 82% in 6 Months
By Eric Bush · July 17, 2026 · 9 min read
The Bottom of the Market Just Reset
Six months ago, if you asked "what's the cheapest capable AI coding model?" the honest answer was somewhere around $0.14 per million input tokens — DeepSeek V3.2 and similar. That number felt like a floor. Compute costs, provider margins, and quality expectations all seemed to hold it in place.
Today the floor is $0.025 per million input tokens. Nex-N2-Mini, released in late Q2 2026, charges 82% less than the cheapest option from January. Behind it, six models cluster between $0.05 and $0.10, and the entire bottom fifteen of the market fits under $0.15 input. This piece walks through the 15 cheapest coding models in our tracked pricing database and what the collapse means for teams still paying 2025-era rates.
The 15 Cheapest Coding Models (Input Price)
| Rank | Model | Provider | Input $/M | Output $/M |
|---|---|---|---|---|
| 1 | Nex-N2-Mini | Nex AGI | $0.025 | $0.10 |
| 2 | GPT-5 Nano | OpenAI | $0.05 | $0.40 |
| 3 | Granite 4.1 8B | IBM | $0.05 | $0.10 |
| 4 | Laguna XS 2.1 | Poolside | $0.06 | $0.12 |
| 5 | GLM 4.7 Flash | Zhipu | $0.06 | $0.40 |
| 6 | Ring-2.6-1T | inclusionAI | $0.075 | $0.625 |
| 7 | Llama 4 Scout | Meta | $0.08 | $0.30 |
| 8 | Qwen3 30B | Alibaba | $0.08 | $0.28 |
| 9 | DeepSeek V4 Flash | DeepSeek | $0.09 | $0.18 |
| 10 | GPT-4.1 nano | OpenAI | $0.10 | $0.40 |
| 11 | Gemini 2.0 Flash | $0.10 | $0.40 | |
| 12 | Devstral Small | Mistral | $0.10 | $0.30 |
| 13 | MiMo V2 Flash | Xiaomi | $0.10 | $0.30 |
| 14 | MiMo V2.5 | Xiaomi | $0.105 | $0.28 |
| 15 | Qwen3 Coder Next | Alibaba | $0.11 | $0.80 |
Twelve providers appear in the top fifteen. This isn't one company dumping prices — it's a market-wide reset. When the floor moves, it moves for everyone.
Timeline: How the Floor Fell
| Month | Cheapest input $/M | Model at the floor | % drop from Jan |
|---|---|---|---|
| Jan 2026 | $0.14 | DeepSeek V3.1 | — |
| Mar 2026 | $0.10 | Gemini 2.0 Flash, GPT-4.1 nano | -29% |
| May 2026 | $0.075 | Ring-2.6-1T | -46% |
| Jun 2026 | $0.05 | GPT-5 Nano, Granite 4.1 8B | -64% |
| Jul 2026 | $0.025 | Nex-N2-Mini | -82% |
The trend line is unusually clean for a market this competitive: roughly a 20-30% floor reduction each quarter, with the pace accelerating in Q2 2026 as multiple providers converged on the same aggressive pricing strategy.
What Kind of Work Does the New Floor Handle?
The obvious question when a model charges $0.025 per million input tokens is "can it actually do anything useful?" Reasonable answer: yes, for specific classes of work.
Well-suited for cheapest tier ($0.025-$0.10): single-file code completion, autocomplete, format transformations (JSON ↔ YAML), templated code generation (CRUD boilerplate), commit message drafting, simple docstring generation, log analysis, and classification.
Marginal at the cheapest tier: multi-file refactors, tests with realistic assertions, code review for subtle bugs, and anything requiring reasoning across long context.
Still needs mid or top tier: production-critical business logic, security review, complex architectural changes, and workflows where a single hallucination costs real money to recover from.
If Your Team Is Still on 2025 Pricing
Any team that locked in a "cheap tier" model choice in early 2025 and hasn't revisited is paying 3-5x more than necessary for equivalent quality. Concrete example: a workflow generating 100M input tokens per month on DeepSeek V3.1 ($0.14) costs $14/month for input. The same workflow on Nex-N2-Mini ($0.025) costs $2.50 — an 82% reduction with likely-comparable quality on well-suited tasks.
Multiply by the actual token volume of a team pipeline — often 500M-5B input tokens per month across agents and completions — and you're looking at hundreds to thousands of dollars of monthly savings for a couple hours of migration work.
Should You Expect the Floor to Keep Falling?
Probably yes, but at a slower rate. Physical inference cost per token has been falling roughly 30-40% annually because of TSMC capacity expansion, better serving software, and architectural improvements like MoE. Provider margins on the cheap tier are already thin — the price war is real but not infinite.
Realistic forecast: the floor lands at $0.01-$0.02 per million input tokens by mid-2027, then flattens as we hit the actual cost-of-inference wall. That's another 20-60% reduction — meaningful but not another 82%.
Bottom Line
The cheapest capable coding model dropped from $0.14 to $0.025 per million input tokens between January and July 2026 — an 82% collapse in six months. If your team hasn't reviewed model choices this year, you're likely overpaying by a factor of 3-5x on high-volume workloads. Use our cost calculator to compare your current setup against the new floor and see the actual savings on your workload.
Want to calculate exact costs for your project?
Frequently Asked Questions
What is the cheapest AI coding model in July 2026?
Nex-N2-Mini from Nex AGI at $0.025 per million input tokens and $0.10 per million output tokens. This is 82% cheaper than the cheapest capable model available in January 2026 (DeepSeek V3.1 at $0.14 input).
Are cheap AI coding models actually usable for real work?
Yes, for the right kind of work. The $0.025-$0.10 input tier handles autocomplete, format transformations, templated code generation, commit message drafting, log analysis, and classification well. Complex multi-file refactors, security-critical code, and long-context reasoning still need mid or top tier models.
How much can I save by switching from 2025 pricing to 2026 pricing?
For teams still on $0.14/M input models, switching to Nex-N2-Mini or Granite 4.1 8B at $0.025-$0.05 delivers 65-82% savings on input tokens. At 500M-5B input tokens per month typical for coding agent pipelines, this is hundreds to thousands of dollars per month recovered.
Will AI coding model prices keep dropping this fast?
Probably slower going forward. The 20-30% quarterly drops through Q1-Q2 2026 reflect an aggressive price war among cheap-tier providers. Realistic forecast: the floor reaches $0.01-$0.02/M input by mid-2027, then flattens as we hit the actual inference-cost wall. Another 20-60% total reduction, not another 82%.
Which cheap models should I try first for my coding workflow?
Start with Nex-N2-Mini for aggressive cost-cutting on well-structured tasks, or Granite 4.1 8B ($0.05) and GPT-5 Nano ($0.05) for slightly better quality at the same price. DeepSeek V4 Flash ($0.09) is a strong all-rounder that many teams already use in production. Benchmark all three on your specific workload before committing.
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