Ticket and content classification: what it costs and which AI to use
Label a huge stream of tickets, reviews, emails or posts: topic, urgency, spam, language, sentiment. Anyone with half a million or more short items a month to sort.
The short answer
At 500,000 items a month, we estimate $11.30 on DeepSeek V4.1 Flash (the cheapest model that cleared our quality bar), $91.13 on Mistral Large 3 2512, and $1,001 on GPT-5.5. The flagship costs 11x the middle pick. Judged on classification tasks: the label has to match, so cheap models often tie expensive ones.
Simulate your ticket and content classification
Pick a job, set how much of it you do, and see what every model would cost. Defaults are typical, not yours. Change them.
Prompt, history, documents
What the model writes
Advanced: caching, reasoning, retries, discounts
Share that can use cached-input prices where a model offers them
1 = none. 2 = hidden thinking doubles billed output
Extra calls on top of the base count
Batch jobs or committed spend. Check your provider; we assume none by default
Lowest benchmark score a model can have and still be picked. Higher is stricter.
Limit to certain providers
Untick any provider you cannot use, for data-residency, contract or policy reasons. Picks are recalculated.
500K items a month, three ways to pay
Every model here cleared a score of 8.0 out of 10 on the classify benchmark tasks, ran without errors and fits a 8K-token window. 41 of 386 priced models qualify.
Cheapest model that clears the bar.
DeepSeek V4.1 Flash
- Per item
- $0.0000
- Benchmark
- 10.00 / 10 · 3 prompts
- Context
- 1.05M tokens
Priced near the middle of the models that clear the bar; best score there.
Mistral Large 3 2512
- Per item
- $0.0002
- Benchmark
- 10.00 / 10 · 3 prompts
- Context
- 262K tokens
What many people reach for first.
GPT-5.5
- Per item
- $0.0020
- Benchmark
- 10.00 / 10 · 3 prompts
- Context
- 1.05M tokens
Choosing GPT-5.5 over Mistral Large 3 2512 costs $910 more a month, $10,922 a year (11x the price).
Both scored 10.00 out of 10 on this kind of work. The extra money buys safety margin our benchmark cannot measure: it is 24 short prompts, and most passing models score near the top. If a wrong answer is costly for you, that margin can be worth it. Test on your own data before you decide.
If it grows
Pay-per-use cost scales in a straight line. Monthly cost at 1x, 3x, 10x and 100x today's volume.
| Model | 1x · 500K | 3x · 1.5M | 10x · 5M | 100x · 50M |
|---|---|---|---|---|
| DeepSeek V4.1 Flash | $11.30 | $33.91 | $113 | $1,130 |
| Mistral Large 3 2512 | $91.13 | $273 | $911 | $9,113 |
| GPT-5.5 | $1,001 | $3,004 | $10,013 | $100,125 |
What a budget buys
- DeepSeek V4.1 Flash4.4Mitems a month, about 147K a day
- Mistral Large 3 2512549Kitems a month, about 18K a day
- GPT-5.550Kitems a month, about 1,664 a day
Every model, priced for your workload
41 models, 3 hidden because their window is smaller than 8K tokens.
| Model | A month | Per item | Benchmark | Context |
|---|---|---|---|---|
| DeepSeek V4.1 Flash DeepSeekBudget pick | $11.30 | $0.0000 | 10.00 (3) | 1.05M |
| DeepSeek V4 Flash 0423 DeepSeek | $16.65 | $0.0000 | 10.00 (3) | 1.05M |
| Llama 4 Scout Meta | $21.26 | $0.0000 | 10.00 (3) | 1.31M |
| GLM 5.3 Z Ai | $24.06 | $0.0000 | 10.00 (3) | 1.05M |
| Ministral 3 8B 2512 Mistral AI | $25.54 | $0.0001 | 10.00 (3) | 262K |
| Qwen3.8 Flash Alibaba | $27.53 | $0.0001 | 10.00 (3) | 1M |
| Mistral Small 4 Mistral AI | $28.24 | $0.0001 | 10.00 (3) | 262K |
| GLM 5.3 Flash Z Ai | $28.65 | $0.0001 | 10.00 (3) | 1.05M |
| Qwen3.8 27B Alibaba | $37.41 | $0.0001 | 10.00 (3) | 1.02M |
| GPT-5.4 Nano OpenAI | $40.35 | $0.0001 | 10.00 (3) | 400K |
| GLM 5.2 Z Ai | $42.08 | $0.0001 | 10.00 (3) | 1.05M |
| MiniMax M2.5 Minimax | $50.25 | $0.0001 | 10.00 (3) | 205K |
Benchmark = mean judge score out of 10 on the classify prompts of the Model Playground, with the number of prompts in brackets. Models marked n/a have no benchmark run, so we do not guess their quality. How the benchmark works.
What we assumed
- Half a million items a month.
- Each item is about 300 words once the label instructions are added, around 450 tokens.
- The answer is a short label, about 12 tokens.
- 30% of input (the label instructions) repeats.
These are typical numbers, not measurements of your business. Edit them in the simulator above.
What drives the cost
Pure volume. Each item is tiny and the answer is one word, so price per input token decides everything. This is where specialised decision models can undercut chat models.
Watch out for
- For a bare label, compare against decision models in the Decision Model Cost Lab. They return typed answers with free output.
- Check accuracy on a few hundred of your own items before moving a big stream to a cheaper model.
Questions people ask
How much will ticket and content classification cost per month?
At 500,000 items a month, we estimate $11.30 a month on DeepSeek V4.1 Flash, the cheapest model that clears our quality bar for this job. Mistral Large 3 2512 costs $91.13 and GPT-5.5 costs $1,001. These are estimates from the assumptions listed on this page, not a quote. Change the numbers to match your own volume.
What is the cheapest AI model for ticket and content classification?
On current OpenRouter prices, DeepSeek V4.1 Flash from DeepSeek is the cheapest model that cleared our bar of 8.0 out of 10, scoring 10.0/10 on 3 benchmark prompts for this kind of work. The benchmark is small, so treat it as a shortlist and test on your own data before switching.
Is it worth paying for a flagship model for ticket and content classification?
On our benchmark, GPT-5.5 scored 10.0/10 on this kind of work, and a model priced near the middle of the models that cleared the bar, Mistral Large 3 2512, scored 10.0/10, while the flagship costs 11x as much. A flagship buys safety margin the benchmark cannot measure. If a wrong answer is expensive for you, that can be worth paying for. If not, you are probably overpaying.
What happens to the cost if ticket and content classification grows ten times?
Pay-per-use pricing scales in a straight line, so ten times the items is ten times the bill. Use the growth table on this page to see 3x, 10x and 100x for the same three models.
What makes ticket and content classification expensive?
Pure volume. Each item is tiny and the answer is one word, so price per input token decides everything. This is where specialised decision models can undercut chat models.
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