Ministral 3 14B Base 2512 vs GPT-5 Pro
At a Glance
| Compare |  Ministral 3 14B Base 2512Mistral AI |  GPT-5 ProOpenAI |
|---|---|---|
| Pricing and Limits | ||
| Input priceFrom · USD / 1M tokens | Not reported | $7.50Openrouter ↗ · Sep 3, 2026 |
| Output priceFrom · USD / 1M tokens | Not reported | $60.00Openrouter ↗ · Sep 3, 2026 |
| Context windowMaximum documented tokens | 262K | 400K |
| Model facts checked | Aug 28, 2026View model evidence → | Sep 3, 2026View model evidence → |
Token prices are the lowest available sourced USD rates; input and output may use different providers. Cost ranking estimates output spend on LiveBench, not a full request bill. Ranking methodology →
Available Benchmarks
Side-by-Side Facts
| Field | Ministral-3-14B-Base-2512 | GPT-5 Pro |
|---|---|---|
| Developer | Mistral AI | OpenAI |
| Family | Ministral 3 14b Base 2512 | Gpt 5 |
| Model | Ministral-3-14B-Base-2512 | GPT-5 Pro |
| Version | Ministral-3-14B-Base-2512 | GPT-5 Pro |
| Lifecycle | active | active |
| Released | Unknown | 2025-10-06 |
| Knowledge cutoff | Unknown | 2024-09-30 |
| Input modalities | Text, Image | Text, Image |
| Output modalities | Text | Text |
| Context window | 262K | 400K |
| Total parameters | 13.9B | Unknown |
| Active parameters | Unknown | Unknown |
| License | apache-2.0 | Unknown |
| Open weights | Yes | No |
| API available | Unknown | Yes |
| Self-hostable | Yes | No |
| Provider access | Unknown | Openai (Standard), Openrouter (Standard) |
| Capabilities | generation | chat, generation, reasoning, structured_outputs, tools |
Ministral 3 14B Base 2512 Capabilities
GPT-5 Pro Capabilities
Related Comparisons
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|---|---|---|---|
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Ministral-3-14B-Base-2512Mistral AI | vs |  GLM-5.3Z.ai | cross-developer peerstext |
Ministral-3-14B-Base-2512Mistral AI | vs |  Hy4 previewTencent | cross-developer peerstext |
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Ministral-3-14B-Base-2512Mistral AI | vs | Mistral Large 3Mistral AI | developer peersimage, text |
Primary Evidence
Sources and Freshness
Questions
Ministral 3 14B Base 2512 vs GPT-5 Pro FAQs
Is Ministral 3 14B Base 2512 or GPT-5 Pro better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Ministral 3 14B Base 2512 and GPT-5 Pro, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, Ministral 3 14B Base 2512 or GPT-5 Pro?+
Only GPT-5 Pro has a directly sourced input price: $7.50 per million tokens. Only GPT-5 Pro has a directly sourced output price: $60.00 per million tokens.
Which has a larger context window, Ministral 3 14B Base 2512 or GPT-5 Pro?+
GPT-5 Pro has the larger sourced context window. Ministral 3 14B Base 2512 supports 262K and GPT-5 Pro supports 400K.
Which performs better in benchmarks, Ministral 3 14B Base 2512 or GPT-5 Pro?+
There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.
Can Ministral 3 14B Base 2512 or GPT-5 Pro be self-hosted?+
Ministral 3 14B Base 2512 is the only model in this pair currently marked as self-hostable. Ministral 3 14B Base 2512 is open weight; GPT-5 Pro is not marked open weight.
Can Ministral 3 14B Base 2512 and GPT-5 Pro understand images?+
Ministral 3 14B Base 2512 is documented with image input; GPT-5 Pro is documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, Ministral 3 14B Base 2512 or GPT-5 Pro?+
Neither has a larger sourced maximum output. Ministral 3 14B Base 2512 is — and GPT-5 Pro is 272K.
Do Ministral 3 14B Base 2512 and GPT-5 Pro support reasoning and tool use?+
Ministral 3 14B Base 2512: image input. GPT-5 Pro: reasoning, tool calling, and image input. Feature support does not establish relative quality.
Which is available from more inference providers, Ministral 3 14B Base 2512 or GPT-5 Pro?+
Ministral 3 14B Base 2512 has 0 sourced provider routes; GPT-5 Pro has 2, so GPT-5 Pro has broader tracked availability.
Which offers better value, Ministral 3 14B Base 2512 or GPT-5 Pro?+
There is no universal value winner. Compare the input and output prices above with the matched benchmark result for your workload: cheaper tokens can be offset by different quality, token usage, latency, or provider availability.