Mistral Medium 3.5 vs Qwen3 32B
Pick up to 3 models · pricing, context and capabilities · simulate your product cost
Data updated on September 30, 2026· 217 models
Mistral Medium 3.5 is a dense 128B instruction-following model from Mistral AI.
- Reasoning estimated
- Speed estimated
- Input
- Output
- Context
- ▲262 K tokens
- Max output
- ▲210 K
- Input, $ per 1M tokens
- $1.50
- Output, $ per 1M tokens
- $7.50
- Cache read, $ per 1M
- —
- Batch (input / output)
- $0.750 / $3.75
- Tool calling
- Yes
- Released
- ▲05/01/2026
- Knowledge cutoff
- —
- API id
- mistralai/mistral-medium-3-5
Qwen3-32B is a dense 32.8B parameter causal language model from the Qwen3 series, optimized for both complex reasoning and efficient dialogue.
- Reasoning estimated
- ▲
- Speed estimated
- Input
- Output
- Context
- 131 K tokens
- Max output
- 16 K
- Input, $ per 1M tokens
- ▲$0.080
- Output, $ per 1M tokens
- ▲$0.280
- Cache read, $ per 1M
- —
- Batch (input / output)
- —
- Tool calling
- Yes
- Released
- 04/01/2025
- Knowledge cutoff
- 2025-04
- API id
- qwen/qwen3-32b
Which is the better API choice: Mistral Medium 3.5 vs Qwen3 32B?
- Qwen3 32B: cheapest input (95% less than Mistral Medium 3.5)
- Qwen3 32B: cheapest output
- Mistral Medium 3.5: largest context (262 K)
- Mistral Medium 3.5: the newest (05/01/2026)
- Qwen3 32B: most reasoning (estimated)
Qwen3 32B costs 95% less on input and 96% less on output than Mistral Medium 3.5 ($0.080 / $0.280 versus $1.50 / $7.50 per million tokens). Mistral Medium 3.5 accepts more context (262 K). On capabilities, Mistral Medium 3.5 accepts images; Qwen3 32B has a reasoning mode. Mistral Medium 3.5 offers a batch tier at half price for jobs that do not need an immediate answer.
What would your product cost?
Estimate the monthly cost with your app's real volume. List prices, no cache or batch discounts.
With Qwen3 32B you save $50.18 a month versus Mistral Medium 3.5 (96% 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)
- 1Qwen3 32B Qwen$0.006
- 2Mistral Medium 3.5 Mistral$0.114
- 3Claude Sonnet 5.5 Anthropic$0.152
- 4Claude Sonnet 5 Anthropic$0.152
- 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: Mistral Medium 3.5 vs Qwen3 32B?
Qwen3 32B costs 95% less on input and 96% less on output than Mistral Medium 3.5 ($0.080 / $0.280 versus $1.50 / $7.50 per million tokens). Mistral Medium 3.5 accepts more context (262 K). On capabilities, Mistral Medium 3.5 accepts images; Qwen3 32B has a reasoning mode. Mistral Medium 3.5 offers a batch tier at half price for jobs that do not need an immediate answer.
Which is cheaper: Mistral Medium 3.5 and Qwen3 32B?
Qwen3 32B is cheaper: $0.080 per million input tokens and $0.280 per million output tokens, versus $1.50 / $7.50 for Mistral Medium 3.5.
Which has more context: Mistral Medium 3.5 and Qwen3 32B?
Mistral Medium 3.5 accepts 262 K tokens of context; Qwen3 32B accepts 131 K.
Which is newer: Mistral Medium 3.5 and Qwen3 32B?
Mistral Medium 3.5 was released on 05/01/2026; Qwen3 32B on 04/01/2025.
What would 10,000 requests a month cost with Mistral Medium 3.5 and Qwen3 32B?
With 1,500 input and 400 output tokens per request: Mistral Medium 3.5: $52.50; Qwen3 32B: $2.32 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.