GPT-6 Luna vs Qwen3.8-Flash
GPT-6 Luna is the cheaper of the 2: for the same tokens, 3 read for each 1 written, Qwen3.8-Flash costs 1.1 times as much. Below are both price lists, what 8 everyday jobs cost a month on each, and how many tokens the same text takes on each, which can change the answer.
- For the same tokens
- GPT-6 Luna is cheaper; Qwen3.8-Flash costs 1.1 times as much
- Cheaper to read
- GPT-6 Luna, $0.10 against $0.15
- Cheaper to write
- Qwen3.8-Flash, $0.47 against $0.50
- Scores higher
- Not known, Qwen3.8-Flash has no independent score yet
- Larger window
- Not listed for Qwen3.8-Flash
Price per million tokens, side by side
In US dollars, as each maker prints them. The better figure in each row is green.
| GPT-6 LunaOpenAI | Qwen3.8-FlashAlibaba | |
|---|---|---|
| InputTokens the model reads | $0.10 | $0.15 |
| Cached inputRead again from the cache | $0.01 | $0.016 |
| Cache writePutting text in the cache | $0.125 | Not listed |
| OutputTokens it writes, thinking included | $0.50 | $0.47 |
| Blend 3:13 tokens read for each 1 written | $0.20 | $0.23 |
| Batch inputAnswers collected later | $0.05 | Not listed |
| Batch output | $0.25 | Not listed |
| Long prompt inputAbove 272K on GPT-6 Luna | $0.20 | $0.15 |
| Long prompt outputThe standard price where there is no long-prompt price | $0.75 | $0.47 |
| Context windowTokens it holds at once | 1.05M | Not listed |
| Capability scoreEpoch Capabilities Index; GPT-5 is 150 | 156 | Not listed |
| Longest answerTokens it writes in 1 reply | 128K | Not listed |
The same text, counted by each maker
A price per token means little until you know how many tokens your text is. Here is our lesson How AI writes, about 1,700 words of English, counted the way each maker counts it, and what it costs to send it once.
GPT-6 Luna
about 2,100 tokens
Sent once: 0.021 cents at $0.10 per million
GPT-5.6 is counted with o200k_base, the tokenizer OpenAI publishes for it, so its count is exact. OpenAI has not published the tokenizer of GPT-6, so its count is the same o200k_base figure, marked as about.
Qwen3.8-Flash
about 2,100 tokens
Sent once: 0.032 cents at $0.15 per million
Counted with the tokenizer Alibaba publishes with its open Qwen3.8 models. Alibaba does not say its API models use the same one, so the count is marked as about.
What 8 everyday jobs cost a month on each
Each job at its usual number of runs a day, for 30 days, at the standard price. The cheaper of the 2 is green; open any job in the calculator to change it.
| Job | GPT-6 Luna | Qwen3.8-Flash | Difference |
|---|---|---|---|
| A chat question300 in, 500 out, 100 a day | 84 cents0.028 cents a run | 84 cents0.028 cents a run | The same |
| A hard question, with thinking300 in, 1,400 out, 100 a day | $2.190.073 cents a run | $2.110.07 cents a run | 1 times |
| A long report, summarised60,000 in, 2,000 out, 20 a day | $4.200.7 cents a run | $5.960.99 cents a run | 1.4 times |
| A 40-turn agent task2,800,000 in, 40,000 out, 10 a day | $21.967.3 cents a run | $30.3410 cents a run | 1.4 times |
| A support bot's reply4,000 in, 300 out, 2,000 a day | $22.200.037 cents a run | $28.380.047 cents a run | 1.3 times |
| Sort a message into a category250 in, 5 out, 50,000 a day | $41.250.0028 cents a run | $59.770.004 cents a run | 1.4 times |
| Read an invoice into fields1,500 in, 250 out, 1,000 a day | $8.250.027 cents a run | $10.270.034 cents a run | 1.2 times |
| Review a pull request25,000 in, 4,500 out, 50 a day | $7.130.48 cents a run | $8.800.59 cents a run | 1.2 times |
Your own job on both
Start from a job, then set its size, how often it runs and whether the answers can wait. Both bills follow every change.
A short question and a few paragraphs back.
about 230 words
Instructions or documents the model has read before cost far less the second time.
about 380 words
A month of this job
- GPT-6 Luna84 cents
0.028 cents a run
- Qwen3.8-Flash84 cents
0.028 cents a run
The 2 cost the same for this job, counted in tokens.
This job on every modelWhy the price per token is only the start
Every maker prints 2 main prices: one for the tokens a model reads (input) and one for the tokens it writes (output). On most current models writing costs 3 to 5 times as much as reading, so which model is cheaper can depend on the job. A job that reads a long document and writes a line pays mostly the input price; a chat that writes paragraphs pays mostly the output price. That is why each comparison prices 8 jobs and not one figure.
The same text is not the same number of tokens on every model. Each maker cuts text its own way, and Anthropic says its models from Claude 4.7 on produce about 30 percent more tokens for the same text than earlier ones. A model with the lower price per token can still send the larger bill, so each comparison counts one of our lessons the way both makers count it.
Discounts change the order too. Work that can wait costs half on a batch at the makers that offer one, and text read again from a cache costs a quarter of the input price or less on every current model here. The price table on each comparison shows who offers what.
Thinking is billed as output, and models differ in how much they think and how long they answer. A price list cannot show that. Before you switch, run the same 10 tasks on both models and compare the bills.
Questions
- Which is cheaper, GPT-6 Luna or Qwen3.8-Flash?
- It depends on the job. GPT-6 Luna is cheaper to read, $0.10 per million tokens against $0.15, and Qwen3.8-Flash is cheaper to write, $0.47 per million against $0.50. A job that mostly reads favours GPT-6 Luna; one that writes long answers favours Qwen3.8-Flash.
- Which is better, GPT-6 Luna or Qwen3.8-Flash?
- GPT-6 Luna scores 156 on the Epoch Capabilities Index, an independent score from Epoch AI that combines over 50 benchmarks (GPT-5 is 150). Qwen3.8-Flash has no independent score yet, so the only fair test is to run the same 10 tasks on both.
- What does a support bot cost a month on GPT-6 Luna and Qwen3.8-Flash?
- At 2,000 replies a day, each reading 4,000 tokens (50 percent of them from cache) and writing 300, it costs $22.20 a month on GPT-6 Luna and $28.38 on Qwen3.8-Flash: Qwen3.8-Flash costs 1.3 times as much for this job.
- What does an AI agent task cost on GPT-6 Luna and Qwen3.8-Flash?
- One 40-turn task that reads 2,800,000 tokens in all, 90 percent of them from cache, and writes 40,000, costs 7.3 cents on GPT-6 Luna and 10 cents on Qwen3.8-Flash. At 10 tasks a day that is $21.96 and $30.34 a month.
- Does the same text take the same number of tokens on GPT-6 Luna and Qwen3.8-Flash?
- No. Our lesson "How AI writes", 1,700 words long, is about 2,100 tokens on GPT-6 Luna and about 2,100 on Qwen3.8-Flash. Each maker cuts text its own way, and every extra token is paid for at the model's price.
- Can I pay less on GPT-6 Luna and Qwen3.8-Flash for work that can wait?
- On GPT-6 Luna only: with a batch, where you collect the answers later, it costs $0.05 per million tokens read and $0.25 written. Alibaba's price page lists no batch price for Qwen3.8-Flash.
Sources