Models tested
| Model | Provider | Input $/1M | Output $/1M |
|---|---|---|---|
| Gemini 2.5 Flash-8B | $0.0375 | $0.15 | |
| Mistral Small 3.2 | Mistral | $0.10 | $0.30 |
| GPT-5 nano | OpenAI | $0.10 | $0.40 |
| GPT-4o mini | OpenAI | $0.15 | $0.60 |
| Gemini 2.5 Flash | $0.15 | $0.60 | |
| DeepSeek V3 | DeepSeek | $0.27 | $1.10 |
| GPT-5 mini | OpenAI | $0.40 | $1.60 |
| Gemini 2.5 Pro | $1.25 | $10.00 | |
| o4-mini | OpenAI | $1.10 | $4.40 |
| GPT-4.1 | OpenAI | $2.00 | $8.00 |
| GPT-5 | OpenAI | $1.25 | $10.00 |
| Claude Sonnet 4.6 | Anthropic | $3.00 | $15.00 |
| Claude Opus 4.8 | Anthropic | $5.00 | $25.00 |
The 20 workloads — cheapest model and cost
Costs are monthly totals at the volumes shown. "Runner-up" is the next cheapest option.
| # | Workload | Tokens (in/out) | Volume/mo | Cheapest | $/mo | Runner-up | $/mo |
|---|---|---|---|---|---|---|---|
| 1 | Customer support reply | 800 / 250 | 100,000 | Gemini Flash-8B | $6.75 | Mistral Small | $15.50 |
| 2 | SEO meta description | 400 / 80 | 500,000 | Gemini Flash-8B | $13.50 | Mistral Small | $32.00 |
| 3 | Code review comment | 2,000 / 400 | 10,000 | Gemini Flash-8B | $1.35 | Mistral Small | $3.20 |
| 4 | Document summarization | 4,000 / 800 | 5,000 | Gemini Flash-8B | $1.35 | Mistral Small | $3.20 |
| 5 | SQL query generation | 600 / 150 | 30,000 | Gemini Flash-8B | $1.35 | Mistral Small | $3.15 |
| 6 | Email classification | 300 / 20 | 200,000 | Gemini Flash-8B | $2.85 | Mistral Small | $7.20 |
| 7 | Product description | 300 / 200 | 50,000 | Gemini Flash-8B | $2.06 | Mistral Small | $4.50 |
| 8 | RAG chatbot answer | 3,000 / 400 | 20,000 | Gemini Flash-8B | $3.45 | Mistral Small | $8.40 |
| 9 | Sentiment analysis | 200 / 30 | 500,000 | Gemini Flash-8B | $6.00 | Mistral Small | $14.50 |
| 10 | Content moderation | 150 / 20 | 1,000,000 | Gemini Flash-8B | $8.62 | Mistral Small | $21.00 |
| 11 | Code autocompletion | 500 / 100 | 100,000 | Gemini Flash-8B | $3.38 | Mistral Small | $8.00 |
| 12 | Legal clause extractionquality risk | 5,000 / 1,000 | 1,000 | Gemini Flash-8B | $0.34 | Mistral Small | $0.80 |
| 13 | Meeting transcript summary | 8,000 / 1,500 | 2,000 | Gemini Flash-8B | $1.05 | Mistral Small | $2.50 |
| 14 | Multi-step reasoningquality risk | 2,000 / 2,000 | 5,000 | Gemini Flash-8B | $1.87 | Mistral Small | $4.00 |
| 15 | Language translation | 500 / 500 | 100,000 | Gemini Flash-8B | $9.37 | Mistral Small | $20.00 |
| 16 | Resume screening | 1,500 / 300 | 10,000 | Gemini Flash-8B | $1.01 | Mistral Small | $2.40 |
| 17 | Invoice data extraction | 1,200 / 400 | 20,000 | Gemini Flash-8B | $2.10 | Mistral Small | $4.80 |
| 18 | Recipe / short-form content | 200 / 600 | 50,000 | Gemini Flash-8B | $4.88 | Mistral Small | $10.00 |
| 19 | Bug explanation | 1,000 / 500 | 20,000 | Gemini Flash-8B | $2.25 | Mistral Small | $5.00 |
| 20 | Long-context chatbot | 10,000 / 500 | 5,000 | Gemini Flash-8B | $2.25 | Mistral Small | $5.75 |
Full model comparison — 4 key workloads
The same volume, every model tier.
1. Customer support reply (100K calls/mo)
800 input tokens (conversation history + system prompt), 250 output. This workload fits a mid-complexity chatbot answering product questions.
| Model | $/mo at 100K calls | vs Flash-8B |
|---|---|---|
| Gemini 2.5 Flash-8B | $6.75 | — |
| Mistral Small 3.2 | $15.50 | 2.3× |
| GPT-4o mini | $27.00 | 4.0× |
| DeepSeek V3 | $49.10 | 7.3× |
| GPT-4.1 | $222.50 | 33× |
| Claude Sonnet 4.6 | $615.00 | 91× |
| Claude Opus 4.8 | $1,025.00 | 152× |
2. Content moderation (1M calls/mo)
150 input tokens (user-generated content to classify), 20 output (category label + confidence). High volume, very short responses — this is where budget models shine most.
| Model | $/mo at 1M calls | vs Flash-8B |
|---|---|---|
| Gemini 2.5 Flash-8B | $8.62 | — |
| Mistral Small 3.2 | $21.00 | 2.4× |
| GPT-4o mini | $34.50 | 4.0× |
| DeepSeek V3 | $62.50 | 7.3× |
| GPT-5 | $387.50 | 45× |
| Claude Sonnet 4.6 | $750.00 | 87× |
| Claude Opus 4.8 | $1,250.00 | 145× |
3. RAG chatbot (20K calls/mo)
3,000 input tokens (retrieved context + conversation), 400 output. Medium-complexity use case where retrieved chunk quality matters as much as model quality.
| Model | $/mo at 20K calls | vs Flash-8B |
|---|---|---|
| Gemini 2.5 Flash-8B | $3.45 | — |
| GPT-4o mini | $13.80 | 4.0× |
| DeepSeek V3 | $25.00 | 7.2× |
| Gemini 2.5 Flash | $13.80 | 4.0× |
| Claude Sonnet 4.6 | $300.00 | 87× |
| Claude Opus 4.8 | $500.00 | 145× |
4. Long-context chatbot (5K calls/mo)
10,000 input tokens (long conversation history or document context), 500 output. For document-grounded Q&A where input cost dominates.
| Model | $/mo at 5K calls | vs Flash-8B |
|---|---|---|
| Gemini 2.5 Flash-8B | $2.25 | — |
| GPT-4o mini | $9.00 | 4.0× |
| Gemini 2.5 Flash | $9.00 | 4.0× |
| GPT-5 | $87.50 | 38.9× |
| Claude Sonnet 4.6 | $187.50 | 83.3× |
| Claude Opus 4.8 | $312.50 | 138.9× |
When not to use the cheapest model
Cost wins do not always translate to product wins. The two workloads marked quality risk above deserve specific attention:
- Legal clause extraction (workload 12): Small models miss negation, conditional clauses, and jurisdiction-specific nuances. A missed "not" in a liability clause can cost more than a year's API bill. Minimum: Gemini 2.5 Flash, GPT-4o, or Claude Sonnet.
- Multi-step reasoning (workload 14): 8B-class models reliably struggle with 3+ step chains where each step depends on the last. You may get plausible-sounding wrong answers. Use a reasoning model (o4-mini) or at minimum GPT-4.1.
- Code review for security-critical code: Budget models detect common patterns but miss subtle logic bugs, race conditions, and injection vectors in complex codebases. The cost difference between Flash-8B and GPT-4.1 for 10K reviews is about $220/month — worth it if you're reviewing security-sensitive code.
The routing strategy
The most effective cost strategy for a multi-feature app is model routing by task type. A typical SaaS might look like:
Short generation, descriptions, meta → Gemini Flash-8B or GPT-5 nano
User-facing chat, support responses → GPT-4o mini or Gemini 2.5 Flash
Complex reasoning, agentic tasks → o4-mini or GPT-4.1
Legal, high-stakes extraction → Claude Sonnet 4.6 or Gemini 2.5 Pro
Internal tools, summaries → DeepSeek V3 (very cost-effective)
This routing approach typically cuts total AI spend by 60–80% versus using a single mid-tier model for everything, with no perceptible quality change in most user-facing features.
FAQ
Which AI model is cheapest for customer support?
At 100,000 calls/month (800 input + 250 output tokens each), Gemini 2.5 Flash-8B costs $6.75/mo vs $27.00 for GPT-4o mini and $615 for Claude Sonnet 4.6. For simple FAQ-style support, Flash-8B is adequate. For complex escalation handling, step up to Flash or GPT-4o mini.
Is the cheapest AI model good enough for production?
Depends on the task. For classification, moderation, SEO descriptions, and structured extraction, ultra-budget models perform comparably to GPT-4o. For multi-step reasoning, legal analysis, or nuanced content generation, cheap models produce noticeably worse output.
What does content moderation cost at 1 million requests per month?
At 1M calls/month with 150 input + 20 output tokens each: Gemini 2.5 Flash-8B $8.62/mo, GPT-4o mini $34.50/mo, DeepSeek V3 $62.50/mo, Claude Sonnet 4.6 $750/mo, Claude Opus 4.8 $1,250/mo.
Should I use different models for different features in my app?
Yes. Routing by task type is common and effective. Use Flash-8B or Mistral Small for classification, moderation, and short-form generation. Use GPT-4o or Claude Sonnet for user-facing chat. Reserve Opus or o4 only for high-stakes reasoning. This can reduce your AI bill by 60–80% with no noticeable quality drop in most features.
How do I calculate AI API cost for my use case?
Multiply input tokens by the input price per 1M, add output tokens multiplied by the output price per 1M, then multiply by your monthly call volume. Use APICostCalc's token cost calculator for any model.
What workloads justify paying for premium models like Claude Opus 4.8?
Legal document review, complex multi-step autonomous agents, nuanced creative writing, and tasks where quality directly drives revenue. At $5.00/$25.00 per 1M, Opus 4.8 is 130× more expensive than Flash-8B on output — only justifiable when quality is measurably worth the premium.
What is the cheapest model for RAG chatbots?
At 20K calls/month with 3,000 input + 400 output tokens: Flash-8B $3.45/mo, GPT-4o mini $13.80/mo, DeepSeek V3 $25.00/mo. Flash-8B is cheapest but for RAG with complex retrieved context, answer quality may suffer — test before committing.
Does model cost scale linearly with usage?
Yes — all token-based pricing is purely linear. There are no volume discounts at most providers until you negotiate enterprise contracts, typically above $10K/month spend.
Is GPT-5 nano cheaper than Gemini Flash-8B?
Similar range. GPT-5 nano is $0.10/$0.40 per 1M vs Flash-8B at $0.0375/$0.15. Flash-8B is cheaper per token. GPT-5 nano may have an edge on tasks optimised for OpenAI models.
How much cheaper is DeepSeek V3 than GPT-4o mini?
DeepSeek V3 ($0.27/$1.10) is roughly 2–5× more expensive than Flash-8B and competitive with GPT-4o mini on short tasks. On longer-context workloads, it can cost more than GPT-4o mini because input price scales quickly at $0.27/1M vs $0.15/1M.