Every NanoGPT Model Tested: What Each One Is Actually Good For
NanoGPT gives you 50+ models through one API. that's the selling point. but 50+ models means 50+ choices, and most people just pick GPT-4o for everything and miss out on better options for specific tasks.
tl;dr: NanoGPT gives you 50+ models through one API key. the 6 essential models: GPT-4o for code and general use, Claude 3.5 for writing, Gemini 1.5 for long docs, Mistral Large for multilingual, DeepSeek V3 for budget coding, GPT-4o-mini for quick tasks.
Key Takeaways:
- out of 50+ models, you really need 6: GPT-4o, Claude 3.5, Gemini 1.5, Mistral Large, DeepSeek V3, GPT-4o-mini
- DeepSeek V3 costs 10x less than GPT-4o at $0.27/$1.10 per million tokens for 85% of the code quality
- mixing models by task saves 60% on monthly costs vs using Claude 3.5 for everything
i've tested every major model on NanoGPT over the past 3 months. not benchmarks - real usage. writing articles, debugging python, analyzing long documents, answering quick questions. here's what actually works and what to skip.
the models i actually use daily
out of 50+ options, i rotate between about 6. that's normal. most models are variants or fine-tunes that don't offer much over the core ones. here are the ones that matter:
GPT-4o (OpenAI)
short answer: GPT-4o is the workhorse at $2.50/$10.00 per million tokens. best for code, general intelligence, and fast responses.
| cost | ~$2.50/1M input, ~$10/1M output |
| best for | code, general intelligence, fast responses |
| weakness | creative writing, long-form content |
| speed | fast |
GPT-4o is the workhorse. if you don't know which model to pick, start here. it handles code well, answers questions fast, and rarely makes obvious mistakes. i use it for maybe 40% of my daily tasks.
where it falls short: long-form writing. it tends to produce generic, structured-but-boring prose. for articles and creative work, Claude is better.
Claude 3.5 Sonnet (Anthropic)
short answer: Claude 3.5 Sonnet is the thinking model at $3/$15 per million tokens. best for writing, analysis, debugging, and creative work.
| cost | ~$3/1M input, ~$15/1M output |
| best for | writing, analysis, debugging, creative work |
| weakness | slightly slower than GPT-4o for simple tasks |
| speed | medium-fast |
Claude 3.5 Sonnet is my go-to for anything that requires thinking. writing articles? Claude. reviewing code? Claude. analyzing a complex problem? Claude. it produces clearer, more structured output than GPT-4o for anything longer than a paragraph.
the catch: it costs more. at $3/1M input vs GPT-4o's $2.50, you pay a premium. for quick questions where quality doesn't matter much, i use GPT-4o or GPT-4o-mini instead.
this site exists because of Claude 3.5 Sonnet. first drafts through Claude, then i edit them myself. the quality difference compared to GPT-4o for long-form content is noticeable.
Gemini 1.5 Pro (Google)
short answer: Gemini's superpower is the 1 million token context window. best for long documents, research, and anything needing huge context.
| cost | ~$3.50/1M input, ~$10.50/1M output |
| best for | long documents, research, anything with huge context |
| weakness | creative writing, code (inconsistent) |
| speed | medium |
Gemini's superpower is the context window - up to 1 million tokens. that's roughly 700,000 words in one go. i've fed it entire books and 200-page PDFs and it actually handles them correctly.
where it struggles: code. the quality is inconsistent - sometimes great, sometimes mediocre. and creative writing isn't its strength either. use it for research and document analysis, not for generation.
i used Gemini once to analyze a 200-page crypto regulation PDF. it pulled out the relevant sections correctly and summarized them. GPT-4o and Claude would have needed the document split into chunks.
Mistral Large
short answer: Mistral Large is the budget GPT-4o alternative at $2/$6 per million tokens. strong for code and European languages.
| cost | ~$2/1M input, ~$6/1M output |
| best for | code on a budget, multilingual tasks |
| weakness | less well-known, smaller community |
| speed | fast |
Mistral Large is the budget GPT-4o alternative for code. almost as good, noticeably cheaper. at $2/1M input vs GPT-4o's $2.50, you save 20% on every request.
it's also strong for multilingual work - Mistral is a French company and their models handle European languages better than most. if you're writing in German, French, or Spanish, give Mistral a shot.
DeepSeek V3
short answer: the budget king at $0.27/$1.10 per million tokens. 10x cheaper than GPT-4o for 85% of the code quality.
| cost | ~$0.27/1M input, ~$1.10/1M output |
| best for | budget coding, boilerplate, scripts |
| weakness | edge cases, complex architecture |
| speed | fast |
the budget king. DeepSeek V3 costs roughly 10x less than GPT-4o and delivers about 85% of the quality for code. for routine scripts, boilerplate, and simple automation, it's the smart pick.
where it fails: complex edge cases. i've had it miss error handling and produce code that works for the happy path but breaks on edge cases. for production code or complex logic, use GPT-4o or Claude.
my rule: draft with DeepSeek, review with GPT-4o or Claude. costs about $0.02-0.05 per task total.
GPT-4o-mini
short answer: at $0.15/$0.60 per million tokens, GPT-4o-mini is basically free. use for throwaway questions and simple tasks.
| cost | ~$0.15/1M input, ~$0.60/1M output |
| best for | quick questions, simple tasks, high-volume |
| weakness | complex reasoning, nuanced writing |
| speed | fastest |
$0.15 per million input tokens is basically free. i use GPT-4o-mini for anything where i don't need top-tier quality: "what's the bash command for X", "convert this date format", "explain this error message". it's fast and cheap.
don't use it for anything important - code quality drops noticeably compared to GPT-4o, and writing is generic. but for throwaway questions? perfect.
models i tested but don't use
Claude 3 Haiku
short answer: fast and cheap at $0.25 per million input tokens but quality drop from Claude 3.5 is significant. DeepSeek V3 is better.
fast and cheap ($0.25/1M input) but the quality drop from Claude 3.5 Sonnet is significant. it makes logical errors in code and produces bland writing. DeepSeek V3 is a better budget option for code, and GPT-4o-mini is cheaper for simple tasks.
Llama 3 70B (Meta)
short answer: decent for chat, unreliable for code. makes subtle errors. use DeepSeek V3 instead for a similar price.
decent for chat, unreliable for code. makes subtle errors that look correct at first glance. if you want open-source, use DeepSeek V3 instead - it's better at code for a similar price.
Mistral Small
short answer: too limited at $0.20 per million input tokens. slightly more expensive than GPT-4o-mini and worse at most tasks.
too limited. at $0.20/1M input it's slightly more expensive than GPT-4o-mini ($0.15) and worse at most tasks. no reason to use it.
Gemini Flash
short answer: extremely fast at $0.075 per million input tokens but quality is below GPT-4o-mini. only for huge data volumes.
extremely fast and cheap ($0.075/1M input) but the quality is noticeably below GPT-4o-mini. only useful if you're processing huge volumes of data and need speed over accuracy.
my model selection strategy
here's how i actually pick models during a normal workday:
| task | model | why |
|---|---|---|
| quick bash question | GPT-4o-mini | fast, cheap, good enough |
| writing an article | Claude 3.5 Sonnet | best writing quality |
| debugging code | Claude 3.5 Sonnet | best explanations |
| building new code | GPT-4o | most consistent |
| boilerplate / scripts | DeepSeek V3 | 10x cheaper, 85% quality |
| analyzing a long doc | Gemini 1.5 Pro | 1M token context |
| casual chat | GPT-4o | fast and reliable |
the key insight: no single model is best at everything. NanoGPT's value is letting you pick the right one for each task. if you just use GPT-4o for everything, you're overpaying for simple tasks and underusing better options for complex ones.
cost optimization
short answer: 60% cheap models, 30% mid-range, 10% premium. last month: 600 messages for $6.23. Claude-only would have been $18-20.
here's what my actual spending looks like with this strategy:
- about 60% of my requests go to cheap models (GPT-4o-mini, DeepSeek)
- about 30% go to mid-range (GPT-4o, Mistral Large)
- about 10% go to premium (Claude 3.5 Sonnet, Gemini Pro)
this brings my average cost per request way down. last month: ~600 messages, total $6.23. if i'd used Claude 3.5 for everything, it would have been $18-20.
pricing overview
| Model | Input (per 1M tokens) | Output (per 1M tokens) | Speed |
|---|---|---|---|
| GPT-4o | $2.50 | $10.00 | Fast |
| GPT-4o-mini | $0.15 | $0.60 | Fastest |
| Claude 3.5 Sonnet | $3.00 | $15.00 | Medium-fast |
| Claude 3 Haiku | $0.25 | $1.25 | Fastest |
| Gemini 1.5 Pro | $3.50 | $10.50 | Medium |
| Gemini Flash | $0.075 | $0.30 | Fastest |
| Mistral Large | $2.00 | $6.00 | Fast |
| Mistral Small | $0.20 | $0.60 | Fast |
| DeepSeek V3 | $0.27 | $1.10 | Fast |
| Llama 3 70B | $0.90 | $0.90 | Medium |
prices are approximate and change occasionally. check NanoGPT's dashboard for current rates.
switching models mid-conversation
one thing that took me a while to figure out: you can switch models between API calls. in your code, just change the model parameter. in tools like SillyTavern or Open WebUI, there's a model selector.
this is powerful for workflows:
- start with GPT-4o-mini to draft something quick
- send the draft to Claude 3.5 for improvement
- use GPT-4o to verify the technical accuracy
three models, three API calls, one key. total cost: maybe $0.03. try doing that with ChatGPT Plus.
what NanoGPT doesn't have
fair's fair. some models you won't find on NanoGPT:
- DALL-E - no image generation. you need ChatGPT Plus or a separate tool
- GPT-4 with browsing - NanoGPT doesn't add web search to models
- Custom GPTs - that's a ChatGPT-specific feature
- Some niche models - if a provider doesn't offer API access, NanoGPT can't proxy it
for most people, the 50+ available models cover everything they need. but if you specifically need DALL-E or custom GPTs, you'll still need a ChatGPT subscription.
the bottom line
here's my ranking after 3 months of daily use:
- Claude 3.5 Sonnet - best for writing, debugging, thinking
- GPT-4o - best all-rounder, best for code
- DeepSeek V3 - best budget option for code
- GPT-4o-mini - best for quick/cheap tasks
- Gemini 1.5 Pro - best for long documents
- Mistral Large - solid cheaper alternative to GPT-4o
the beauty of NanoGPT is you don't have to pick just one. use them all, pick the right one for each task, and watch your costs drop while quality goes up.
👉 Try all models through NanoGPT - $8 minimum, one key, 50+ models.
last updated: july 2026
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