Llama 3.3 70B Instruct vs Apertus 70B Instruct
Compare the listed model data for Llama 3.3 70B Instruct by Meta Llama and Apertus 70B Instruct by KAIST AI. Benchmark and pricing records are not a controlled test and may change.
Data last updated: 2026-10-16. Verify current model details with each provider.
What the listed data says
Llama 3.3 70B Instruct: 128K tokens; Apertus 70B Instruct: 128K tokens. The listed context-window values are equal. Llama 3.3 70B Instruct is listed for coding, agentic workflows, long-context tasks; Apertus 70B Instruct is listed for coding, reasoning, long-context tasks. Shared catalog benchmark entries: MMLU: Llama 3.3 70B Instruct 86.0%; Apertus 70B Instruct 84.0%; MATH: Llama 3.3 70B Instruct 77.0%; Apertus 70B Instruct 82.0%. These records are reference data, not a controlled head-to-head test; verify current pricing and specifications with each provider.
Catalog source links
Use these model and provider links to verify current specifications, pricing, and availability.
Computed differences from catalog data
- The listed context windows are 128K tokens and 128K tokens; the larger is 1× the smaller.
- On shared numeric benchmark entries, MMLU: Llama 3.3 70B Instruct − Apertus 70B Instruct = +2 percentage points (86.0% vs 84.0%); MATH: Llama 3.3 70B Instruct − Apertus 70B Instruct = -5 percentage points (77.0% vs 82.0%).
- The first listed parameter quantities are 70B and 70B; the larger quantity is 1× the smaller. Total and active MoE parameters are not directly equivalent.
- The catalog release dates are December 2024 and September 2025, about 9 months apart at the precision supplied.
Cost example: 1M input and 1M output tokens
A cost example for 1M input plus 1M output tokens cannot be calculated reliably because separate numeric input and output rates are not listed for both models.
Choose Llama 3.3 70B Instruct if…
Choose Llama 3.3 70B Instruct when your task aligns with catalog-listed uses or strengths such as Enterprise text processing at 70B quality, Production chatbots for business, Code assistance, Best performance per dollar in the Llama 3.x family at 70B scale.
Choose Apertus 70B Instruct if…
Choose Apertus 70B Instruct when your task aligns with catalog-listed uses or strengths such as Korean-English bilingual enterprise applications, Academic and research AI in Korea, 70B instruction model from Korea's KAIST — top engineering university, Strong Korean and English bilingual performance.
Llama 3.3 70B Instruct
Latest Llama-3.3 70B — exceptional instruction following, coding, and multilingual capabilities across 8 languages.
Parameters: 70B
Context: 128K tokens
Catalog pricing: Llama 3.3 Community License — free. Third-party: $0.59-0.90/MTok
Apertus 70B Instruct
KAIST AI's 70B instruction model — strong reasoning and academic task performance.
Parameters: 70B
Context: 128K tokens
Catalog pricing: Check KAIST AI for license terms
Feature Comparison — Llama 3.3 70B Instruct vs Apertus 70B Instruct
| Specification | Llama 3.3 70B Instruct | Apertus 70B Instruct |
|---|---|---|
| Provider | Meta Llama | KAIST AI |
| Parameters | 70B | 70B |
| Context window | 128K tokens | 128K tokens |
| Maximum output | Not listed | Not listed |
| Catalog pricing | Llama 3.3 Community License — free. Third-party: $0.59-0.90/MTok | Check KAIST AI for license terms |
| Listed input/output cost per 1M tokens | Separate numeric input/output rates not listed | Separate numeric input/output rates not listed |
| License | Meta Llama 3.3 Community License | Custom |
| Coding support | Listed | Listed |
| Reasoning support | Not listed | Listed |
| Vision input | Not listed | Not listed |
| Multimodal | Not listed | Not listed |
| Open weights | Yes | Yes |
| Benchmark: MMLU | 86.0% | 84.0% |
| Benchmark: MATH | 77.0% | 82.0% |
Figures are transcribed from LITHOVEX model records. Benchmark versions and evaluation setups may differ; pricing and specifications can change. Check each provider's current documentation before making a decision.
Frequently Asked Questions
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Explore these models and related comparisons
Read the Llama 3.3 70B Instruct model profile and Apertus 70B Instruct model profile, or browse the model directory.