Compare AI models
| Specifications | ||
ParametersA rough measure of how big the model is. More parameters usually means more capable and more expensive to run, though it is a poor guide on its own — a smaller, newer model often beats a larger, older one. | 12B | — |
Context windowHow much text the model can hold in mind at once — your question, any documents you attach, the conversation so far, and its own reply. Go past it and the earliest part falls out of view. | 128k | 128k |
| API pricingUSD per 1M tokens · lower wins | ||
Cheapest inputLowest input rate across third-party providers, excluding the lab itself. The cheapest endpoint may run a quantised build or a shorter context — see "Available from" on the model page. | $0.018DekaLLM | — |
Cheapest outputLowest output rate across third-party providers, excluding the lab itself. May come from a different provider than the cheapest input. | $0.027Io Net | — |
| Overview | ||
| Company | Mistral | OpenAI |
| Release date | Jul 18 2024 | Feb 12 2026 |
| Access | Open Weight | Closed |
| Model details | View model | View model |
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Mistral NeMo and GPT-5.3-Codex-Spark don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Mistral NeMo shipped 574 days before GPT-5.3-Codex-Spark, so benchmark comparisons should account for the intervening progress.
Context windows are 128k (Mistral NeMo) vs 128k (GPT-5.3-Codex-Spark). Mistral NeMo is open weight, while GPT-5.3-Codex-Spark is closed.
Direct benchmark comparisons are unavailable — Mistral NeMo and GPT-5.3-Codex-Spark don't publish scores on any of the same benchmarks.