GPT-5.2-Codex vs Mistral Medium 3.5
Pick up to 3 models · pricing, context and capabilities · simulate your product cost
Data updated on September 30, 2026· 217 models
GPT-5.2-Codex is an upgraded version of GPT-5.1-Codex optimized for software engineering and coding workflows.
- Reasoning estimated
- ▲
- Speed estimated
- Input
- Output
- Context
- ▲400 K tokens
- Max output
- 128 K
- Input, $ per 1M tokens
- $1.75
- Output, $ per 1M tokens
- $14.00
- Cache read, $ per 1M
- $0.175
- Batch (input / output)
- —
- Tool calling
- Yes
- Released
- 01/14/2026
- Knowledge cutoff
- 2025-08-31
- API id
- openai/gpt-5.2-codex
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
Which is the better API choice: GPT-5.2-Codex vs Mistral Medium 3.5?
- Mistral Medium 3.5: cheapest input (14% less than GPT-5.2-Codex)
- Mistral Medium 3.5: cheapest output
- GPT-5.2-Codex: largest context (400 K)
- Mistral Medium 3.5: the newest (05/01/2026)
- GPT-5.2-Codex: most reasoning (estimated)
Mistral Medium 3.5 costs 14% less on input and 46% less on output than GPT-5.2-Codex ($1.50 / $7.50 versus $1.75 / $14.00 per million tokens). GPT-5.2-Codex accepts more context (400 K). On capabilities, GPT-5.2-Codex 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 Mistral Medium 3.5 you save $29.75 a month versus GPT-5.2-Codex (36% less).
The 6 cheapest for this scenario (chat, last 12 months)
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- 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)
- 1Mistral Medium 3.5 Mistral$0.114
- 2GPT-5.2-Codex OpenAI$0.133
- 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: GPT-5.2-Codex vs Mistral Medium 3.5?
Mistral Medium 3.5 costs 14% less on input and 46% less on output than GPT-5.2-Codex ($1.50 / $7.50 versus $1.75 / $14.00 per million tokens). GPT-5.2-Codex accepts more context (400 K). On capabilities, GPT-5.2-Codex 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: GPT-5.2-Codex and Mistral Medium 3.5?
Mistral Medium 3.5 is cheaper: $1.50 per million input tokens and $7.50 per million output tokens, versus $1.75 / $14.00 for GPT-5.2-Codex.
Which has more context: GPT-5.2-Codex and Mistral Medium 3.5?
GPT-5.2-Codex accepts 400 K tokens of context; Mistral Medium 3.5 accepts 262 K.
Which is newer: GPT-5.2-Codex and Mistral Medium 3.5?
Mistral Medium 3.5 was released on 05/01/2026; GPT-5.2-Codex on 01/14/2026.
What would 10,000 requests a month cost with GPT-5.2-Codex and Mistral Medium 3.5?
With 1,500 input and 400 output tokens per request: GPT-5.2-Codex: $82.25; Mistral Medium 3.5: $52.50 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.