Llama 4 Maverick 17B 128E vs Ministral 3 14B Reasoning 2512
At a Glance
| Compare | Ministral 3 14B Reasoning 2512Mistral AI | |
|---|---|---|
| Pricing and Limits | ||
| Context windowMaximum documented tokens | 1,000K | 262K |
| Model facts checked | Aug 28, 2026View model evidence → | Aug 28, 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 | Llama-4-Maverick-17B-128E | Ministral-3-14B-Reasoning-2512 |
|---|---|---|
| Developer | Meta | Mistral AI |
| Family | Llama 4 Maverick 17b 128e | Ministral 3 14b Reasoning 2512 |
| Model | Llama-4-Maverick-17B-128E | Ministral-3-14B-Reasoning-2512 |
| Version | Llama-4-Maverick-17B-128E | Ministral-3-14B-Reasoning-2512 |
| Lifecycle | active | active |
| Released | 2025-04-05 | Unknown |
| Knowledge cutoff | Unknown | Unknown |
| Input modalities | Text, Image | Text, Image |
| Output modalities | Text | Text |
| Context window | 1,000K | 262K |
| Total parameters | 401.6B | 13.9B |
| Active parameters | 17B | Unknown |
| License | other | apache-2.0 |
| Open weights | Yes | Yes |
| API available | Unknown | Unknown |
| Self-hostable | Yes | Yes |
| Provider access | Unknown | Unknown |
| Capabilities | chat, generation, tools | chat, generation, reasoning, tools |
Llama 4 Maverick 17B 128E Capabilities
Ministral 3 14B Reasoning 2512 Capabilities
Primary Evidence
Sources and Freshness
Questions
Llama 4 Maverick 17B 128E vs Ministral 3 14B Reasoning 2512 FAQs
Is Llama 4 Maverick 17B 128E or Ministral 3 14B Reasoning 2512 better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Llama 4 Maverick 17B 128E and Ministral 3 14B Reasoning 2512, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, Llama 4 Maverick 17B 128E or Ministral 3 14B Reasoning 2512?+
Neither model has a directly sourced input price in this comparison. Neither model has a directly sourced output price in this comparison.
Which has a larger context window, Llama 4 Maverick 17B 128E or Ministral 3 14B Reasoning 2512?+
Llama 4 Maverick 17B 128E has the larger sourced context window. Llama 4 Maverick 17B 128E supports 1,000K and Ministral 3 14B Reasoning 2512 supports 262K.
Which performs better in benchmarks, Llama 4 Maverick 17B 128E or Ministral 3 14B Reasoning 2512?+
There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.
Can Llama 4 Maverick 17B 128E or Ministral 3 14B Reasoning 2512 be self-hosted?+
Both models have the same recorded self-hosting status: supported. Llama 4 Maverick 17B 128E is open weight; Ministral 3 14B Reasoning 2512 is open weight.
Can Llama 4 Maverick 17B 128E and Ministral 3 14B Reasoning 2512 understand images?+
Llama 4 Maverick 17B 128E is documented with image input; Ministral 3 14B Reasoning 2512 is documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, Llama 4 Maverick 17B 128E or Ministral 3 14B Reasoning 2512?+
Neither has a larger sourced maximum output. Llama 4 Maverick 17B 128E is — and Ministral 3 14B Reasoning 2512 is —.
Do Llama 4 Maverick 17B 128E and Ministral 3 14B Reasoning 2512 support reasoning and tool use?+
Llama 4 Maverick 17B 128E: tool calling and image input. Ministral 3 14B Reasoning 2512: reasoning, tool calling, and image input. Feature support does not establish relative quality.
Which is available from more inference providers, Llama 4 Maverick 17B 128E or Ministral 3 14B Reasoning 2512?+
Llama 4 Maverick 17B 128E has 0 sourced provider routes; Ministral 3 14B Reasoning 2512 has 0, a tie.
Which offers better value, Llama 4 Maverick 17B 128E or Ministral 3 14B Reasoning 2512?+
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.