Qwen3.8 2.4T A95B vs Ministral 8B Instruct 2410
At a Glance
| Compare | Ministral 8B Instruct 2410Mistral AI | |
|---|---|---|
| Pricing and Limits | ||
| Input priceFrom · USD / 1M tokens | $2.00Deepinfra ↗ · Sep 23, 2026 | Not reported |
| Output priceFrom · USD / 1M tokens | $6.00Deepinfra ↗ · Sep 23, 2026 | Not reported |
| Context windowMaximum documented tokens | 262K | 33K |
| 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 | Qwen3.8-2.4T-A95B | Ministral-8B-Instruct-2410 |
|---|---|---|
| Developer | Qwen | Mistral AI |
| Family | Qwen3 8 2 4t A95b | Ministral 8b Instruct 2410 |
| Model | Qwen3.8-2.4T-A95B | Ministral-8B-Instruct-2410 |
| Version | Qwen3.8-2.4T-A95B | Ministral-8B-Instruct-2410 |
| Lifecycle | active | active |
| Released | Unknown | Unknown |
| Knowledge cutoff | Unknown | Unknown |
| Input modalities | Text | Text |
| Output modalities | Text | Text |
| Context window | 262K | 33K |
| Total parameters | 2.4T | 8B |
| Active parameters | 95B | Unknown |
| License | other | other |
| Open weights | Yes | Yes |
| API available | Yes | Unknown |
| Self-hostable | Yes | Yes |
| Provider access | Deepinfra (Standard), Fireworks Ai (Standard), Hugging Face (Standard), Openrouter (Standard), Together Ai (Standard) | Unknown |
| Capabilities | chat, generation, reasoning, tools | chat, generation, tools |
Qwen3.8 2.4T A95B Capabilities
Ministral 8B Instruct 2410 Capabilities
Primary Evidence
Sources and Freshness
Questions
Qwen3.8 2.4T A95B vs Ministral 8B Instruct 2410 FAQs
Is Qwen3.8 2.4T A95B or Ministral 8B Instruct 2410 better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Qwen3.8 2.4T A95B and Ministral 8B Instruct 2410, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, Qwen3.8 2.4T A95B or Ministral 8B Instruct 2410?+
Only Qwen3.8 2.4T A95B has a directly sourced input price: $2.00 per million tokens. Only Qwen3.8 2.4T A95B has a directly sourced output price: $6.00 per million tokens.
Which has a larger context window, Qwen3.8 2.4T A95B or Ministral 8B Instruct 2410?+
Qwen3.8 2.4T A95B has the larger sourced context window. Qwen3.8 2.4T A95B supports 262K and Ministral 8B Instruct 2410 supports 33K.
Which performs better in benchmarks, Qwen3.8 2.4T A95B or Ministral 8B Instruct 2410?+
There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.
Can Qwen3.8 2.4T A95B or Ministral 8B Instruct 2410 be self-hosted?+
Both models have the same recorded self-hosting status: supported. Qwen3.8 2.4T A95B is open weight; Ministral 8B Instruct 2410 is open weight.
Can Qwen3.8 2.4T A95B and Ministral 8B Instruct 2410 understand images?+
Qwen3.8 2.4T A95B is not documented with image input; Ministral 8B Instruct 2410 is not documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, Qwen3.8 2.4T A95B or Ministral 8B Instruct 2410?+
Neither has a larger sourced maximum output. Qwen3.8 2.4T A95B is — and Ministral 8B Instruct 2410 is —.
Do Qwen3.8 2.4T A95B and Ministral 8B Instruct 2410 support reasoning and tool use?+
Qwen3.8 2.4T A95B: reasoning and tool calling. Ministral 8B Instruct 2410: tool calling. Feature support does not establish relative quality.
Which is available from more inference providers, Qwen3.8 2.4T A95B or Ministral 8B Instruct 2410?+
Qwen3.8 2.4T A95B has 5 sourced provider routes; Ministral 8B Instruct 2410 has 0, so Qwen3.8 2.4T A95B has broader tracked availability.
Which offers better value, Qwen3.8 2.4T A95B or Ministral 8B Instruct 2410?+
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.