Pixtral Large vs GPT-5.6 Terra
At a Glance
| Compare |  Pixtral LargeMistral AI |  GPT-5.6 TerraOpenAI |
|---|---|---|
| Intelligence, Cost, and Efficiency | ||
| IntelligenceHigher is better · MM Intelligence v2.5 | UnrankedNot in the 46-model eligible cohort | #13 of 4674.9 score · 3/3 sources · complete |
| CostLower is better · Published-token output estimate | UnrankedNot in the 44-model eligible cohort | #35 of 44$0.266 per LiveBench case |
| EfficiencyHigher is better · MM Efficiency v1.5 | UnrankedNot in the 38-model eligible cohort | #23 of 3851.5 score · 3/3 sources · complete |
| Pricing and Limits | ||
| Input priceFrom · USD / 1M tokens | Not reported | $2.00Openai ↗ · Sep 3, 2026 |
| Output priceFrom · USD / 1M tokens | Not reported | $12.00Openai ↗ · Sep 3, 2026 |
| Context windowMaximum documented tokens | 131K | 1,050K |
| Model facts checked | Aug 29, 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 | Pixtral Large | GPT-5.6 Terra |
|---|---|---|
| Developer | Mistral AI | OpenAI |
| Family | Pixtral Large | Gpt 5 6 |
| Model | Pixtral Large | GPT-5.6 Terra |
| Version | Pixtral Large | GPT-5.6 Terra |
| Lifecycle | deprecated | active |
| Released | 2024-11-18 | Unknown |
| Knowledge cutoff | Unknown | 2026-02-16 |
| Input modalities | Text, Image, Document | Text, Image |
| Output modalities | Text | Text |
| Context window | 131K | 1,050K |
| Total parameters | Unknown | Unknown |
| Active parameters | Unknown | Unknown |
| License | Unknown | Unknown |
| Open weights | No | No |
| API available | No | Yes |
| Self-hostable | No | No |
| Provider access | Unknown | Openai (Standard), Openrouter (Standard) |
| Capabilities | chat, generation, structured_outputs, tools, vision | chat, generation, reasoning, tools |
Pixtral Large Capabilities
GPT-5.6 Terra Capabilities
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Primary Evidence
Sources and Freshness
Questions
Pixtral Large vs GPT-5.6 Terra FAQs
Is Pixtral Large or GPT-5.6 Terra better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Pixtral Large and GPT-5.6 Terra, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, Pixtral Large or GPT-5.6 Terra?+
Only GPT-5.6 Terra has a directly sourced input price: $2.00 per million tokens. Only GPT-5.6 Terra has a directly sourced output price: $12.00 per million tokens.
Which has a larger context window, Pixtral Large or GPT-5.6 Terra?+
GPT-5.6 Terra has the larger sourced context window. Pixtral Large supports 131K and GPT-5.6 Terra supports 1,050K.
Which performs better in benchmarks, Pixtral Large or GPT-5.6 Terra?+
There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.
Can Pixtral Large or GPT-5.6 Terra be self-hosted?+
Both models have the same recorded self-hosting status: unsupported. Pixtral Large is not marked open weight; GPT-5.6 Terra is not marked open weight.
Can Pixtral Large and GPT-5.6 Terra understand images?+
Pixtral Large is documented with image input; GPT-5.6 Terra is documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, Pixtral Large or GPT-5.6 Terra?+
Neither has a larger sourced maximum output. Pixtral Large is — and GPT-5.6 Terra is 128K.
Do Pixtral Large and GPT-5.6 Terra support reasoning and tool use?+
Pixtral Large: tool calling and image input. GPT-5.6 Terra: reasoning, tool calling, and image input. Feature support does not establish relative quality.
Which is available from more inference providers, Pixtral Large or GPT-5.6 Terra?+
Pixtral Large has 0 sourced provider routes; GPT-5.6 Terra has 2, so GPT-5.6 Terra has broader tracked availability.
Which offers better value, Pixtral Large or GPT-5.6 Terra?+
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.