Kimi K2.7 Code vs Qwen3.8 Max Prime
Pick up to 3 models · pricing, context and capabilities · simulate your product cost
Data updated on September 30, 2026· 217 models
MoonshotAI: Kimi K2.7 Code is a coding-focused model in Moonshot AI's Kimi K2 family, built to complete end-to-end programming tasks reliably over long contexts.
- Reasoning estimated
- Speed estimated
- Input
- Output
- Context
- 262 K tokens
- Max output
- ▲236 K
- Input, $ per 1M tokens
- ▲$0.656
- Output, $ per 1M tokens
- ▲$3.30
- Cache read, $ per 1M
- $0.180
- Batch (input / output)
- —
- Tool calling
- Yes
- Released
- 06/12/2026
- Knowledge cutoff
- 2025-01
- API id
- moonshotai/kimi-k2.7-code
Qwen3.8 Max Prime is a higher-throughput variant of Qwen3.8 Max from Alibaba's Qwen team, served as a separate SKU at a higher price point.
- Reasoning estimated
- Speed estimated
- Input
- Output
- Context
- ▲1 M tokens
- Max output
- 131 K
- Input, $ per 1M tokens
- $4.00
- Output, $ per 1M tokens
- $12.00
- Cache read, $ per 1M
- $0.500
- Batch (input / output)
- —
- Tool calling
- Yes
- Released
- ▲09/23/2026
- Knowledge cutoff
- —
- API id
- qwen/qwen3.8-max-prime
Which is the better API choice: Kimi K2.7 Code vs Qwen3.8 Max Prime?
- Kimi K2.7 Code: cheapest input (84% less than Qwen3.8 Max Prime)
- Kimi K2.7 Code: cheapest output
- Qwen3.8 Max Prime: largest context (1 M)
- Qwen3.8 Max Prime: the newest (09/23/2026)
Kimi K2.7 Code costs 84% less on input and 73% less on output than Qwen3.8 Max Prime ($0.656 / $3.30 versus $4.00 / $12.00 per million tokens). Qwen3.8 Max Prime accepts more context (1 M).
What would your product cost?
Estimate the monthly cost with your app's real volume. List prices, no cache or batch discounts.
With Kimi K2.7 Code you save $84.96 a month versus Qwen3.8 Max Prime (79% less).
The 6 cheapest for this scenario (chat, last 12 months)
- 1Lyria 3 Pro Preview Google$0.00
- 2Lyria 3 Clip Preview Google$0.00
- 3Qwen3.7 Flash Qwen$0.97
- 4DeepSeek V4 Flash 0731 DeepSeek$1.55
- 5Ministral 3 3B 2512 Mistral$1.90
- 6Qwen3.5-Flash Qwen$2.02
Paste your prompt: tokens and cost per model
Rough estimate (about 4 characters per token). Nothing is sent to any server.
Cost of sending it 1,000 times (input only)
- 1Kimi K2.7 Code Moonshot$0.050
- 2Claude Sonnet 5.5 Anthropic$0.152
- 3Claude Sonnet 5 Anthropic$0.152
- 4Qwen3.8 Max Prime Qwen$0.304
- 5Claude Opus 5.5 Anthropic$0.304
- 6Claude Opus 5 Anthropic$0.380
- 7Claude Fable 5.1 Anthropic$0.760
- 8Claude Fable 5 Anthropic$0.760
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Frequently asked questions
Which is the better API choice: Kimi K2.7 Code vs Qwen3.8 Max Prime?
Kimi K2.7 Code costs 84% less on input and 73% less on output than Qwen3.8 Max Prime ($0.656 / $3.30 versus $4.00 / $12.00 per million tokens). Qwen3.8 Max Prime accepts more context (1 M).
Which is cheaper: Kimi K2.7 Code and Qwen3.8 Max Prime?
Kimi K2.7 Code is cheaper: $0.656 per million input tokens and $3.30 per million output tokens, versus $4.00 / $12.00 for Qwen3.8 Max Prime.
Which has more context: Kimi K2.7 Code and Qwen3.8 Max Prime?
Qwen3.8 Max Prime accepts 1 M tokens of context; Kimi K2.7 Code accepts 262 K.
Which is newer: Kimi K2.7 Code and Qwen3.8 Max Prime?
Qwen3.8 Max Prime was released on 09/23/2026; Kimi K2.7 Code on 06/12/2026.
What would 10,000 requests a month cost with Kimi K2.7 Code and Qwen3.8 Max Prime?
With 1,500 input and 400 output tokens per request: Kimi K2.7 Code: $23.04; Qwen3.8 Max Prime: $108.00 a month, at list price.
Where do the prices come from and how often are they updated?
From the public catalogs of OpenRouter, models.dev and LiteLLM, which publish each provider's list prices. They sync once a day and the last update date is shown above the comparison.
What does price per million tokens mean?
It is what the provider charges per million tokens you send (input) or the model generates (output). A token is roughly 4 characters. Output almost always costs more than input.
Sources: OpenRouter, models.dev and LiteLLM. Prices in USD per million tokens, list price, no volume discounts. Prompt tokens are an estimate; each provider's tokenizer may differ.