Mistral Large 4 vs Qwen2.5 72B Instruct
Pick up to 3 models · pricing, context and capabilities · simulate your product cost
Data updated on November 14, 2026· 230 models
Mistral Large 4 is a frontier multimodal (text and image input) model from Mistral AI built for reasoning, coding, and agentic workloads.
- Reasoning estimated
- ▲
- Speed estimated
- Input
- Output
- Context
- ▲1 M tokens
- Max output
- ▲262 K
- Input, $ per 1M tokens
- $0.700
- Output, $ per 1M tokens
- $2.10
- Cache read, $ per 1M
- $0.070
- Batch (input / output)
- —
- Tool calling
- Yes
- Released
- ▲10/06/2026
- Knowledge cutoff
- —
- API id
- mistralai/mistral-large-4-0
Qwen2.5 72B is the latest series of Qwen large language models.
- Reasoning estimated
- Speed estimated
- ▲
- Input
- Output
- Context
- 33 K tokens
- Max output
- 16 K
- Input, $ per 1M tokens
- ▲$0.360
- Output, $ per 1M tokens
- ▲$0.400
- Cache read, $ per 1M
- —
- Batch (input / output)
- —
- Tool calling
- Yes
- Released
- 09/19/2024
- Knowledge cutoff
- —
- API id
- qwen/qwen-2.5-72b-instruct
Which is the better API choice: Mistral Large 4 vs Qwen2.5 72B Instruct?
- Qwen2.5 72B Instruct: cheapest input (49% less than Mistral Large 4)
- Qwen2.5 72B Instruct: cheapest output
- Mistral Large 4: largest context (1 M)
- Mistral Large 4: the newest (10/06/2026)
- Mistral Large 4: most reasoning (estimated)
- Qwen2.5 72B Instruct: the fastest (estimated)
Qwen2.5 72B Instruct costs 49% less on input and 81% less on output than Mistral Large 4 ($0.360 / $0.400 versus $0.700 / $2.10 per million tokens). Mistral Large 4 accepts more context (1 M). On capabilities, Mistral Large 4 accepts images; Mistral Large 4 has a reasoning mode.
What would your product cost?
Estimate the monthly cost with your app's real volume. List prices, no cache or batch discounts.
With Qwen2.5 72B Instruct you save $11.90 a month versus Mistral Large 4 (63% 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 V4.1 Flash DeepSeek$1.57
- 5DeepSeek V4 Flash 0731 DeepSeek$1.85
- 6Ministral 3 3B 2512 Mistral$1.90
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)
- 1Claude Haiku 5.5 Anthropic$0.008
- 2Qwen2.5 72B Instruct Qwen$0.027
- 3Mistral Large 4 Mistral$0.053
- 4Claude Sonnet 5.5 Anthropic$0.152
- 5Claude Opus 5.5 Anthropic$0.304
- 6Claude Opus 5 Anthropic$0.380
- 7Claude Fable 5.2 Anthropic$0.608
- 8Claude Fable 5.1 Anthropic$0.760
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See allFrequently asked questions
Which is the better API choice: Mistral Large 4 vs Qwen2.5 72B Instruct?
Qwen2.5 72B Instruct costs 49% less on input and 81% less on output than Mistral Large 4 ($0.360 / $0.400 versus $0.700 / $2.10 per million tokens). Mistral Large 4 accepts more context (1 M). On capabilities, Mistral Large 4 accepts images; Mistral Large 4 has a reasoning mode.
Which is cheaper: Mistral Large 4 and Qwen2.5 72B Instruct?
Qwen2.5 72B Instruct is cheaper: $0.360 per million input tokens and $0.400 per million output tokens, versus $0.700 / $2.10 for Mistral Large 4.
Which has more context: Mistral Large 4 and Qwen2.5 72B Instruct?
Mistral Large 4 accepts 1 M tokens of context; Qwen2.5 72B Instruct accepts 33 K.
Which is newer: Mistral Large 4 and Qwen2.5 72B Instruct?
Mistral Large 4 was released on 10/06/2026; Qwen2.5 72B Instruct on 09/19/2024.
What would 10,000 requests a month cost with Mistral Large 4 and Qwen2.5 72B Instruct?
With 1,500 input and 400 output tokens per request: Mistral Large 4: $18.90; Qwen2.5 72B Instruct: $7.00 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.