Llama 3.3 70B Versatile
Groq • Text
Context Window128K
Knowledge CutoffUnknown
Llama 3.3 70B Versatile vs Mistral Large
Mistral Large for hosted premium quality, Llama 3.3 70B for Groq-hosted high-speed open inference.
Open model page
Mistral Large
Mistral AI • Text
Context Window128K
Knowledge CutoffUnknown
Editorial Verdict
Llama 3.3 70B wins on capability and ecosystem; Mistral Large wins on GDPR compliance.
Llama 3.3 70B outperforms Mistral Large on most benchmarks and benefits from Meta's ecosystem with extensive community support. Mistral Large's advantage is European data residency for GDPR compliance. For capability and ecosystem, Llama 3.3 70B wins. For GDPR-sensitive European deployments, Mistral Large wins.
Llama 3.3 70B Versatile
- Higher benchmark performance across reasoning and coding
- Meta's ecosystem with extensive fine-tuning resources and community
- Widely supported by inference engines and deployment frameworks
Best for: Teams wanting strong capability with Meta's ecosystem support
Mistral Large
- European data residency for GDPR compliance
- Fast inference optimized for European infrastructure
- Good multilingual performance for European language applications
Best for: GDPR-sensitive European enterprise deployments
Pricing sourced from OpenRouter — updates as their catalog changes.
Pricing Comparison
All values pull from OpenRouter and update as their catalog changes.
| Metric | Llama 3.3 70B Versatile | Mistral Large | Winner |
|---|---|---|---|
| Input (per 1M tokens) | Custom | Custom | N/A |
| Output (per 1M tokens) | Custom | Custom | N/A |
| Request fee | N/A | N/A | N/A |
| Image fee | N/A | N/A | N/A |
Cost Estimator
Estimate monthly billing using real OpenRouter prices.
Llama 3.3 70B Versatile Total
VariableMistral Large Total
VariableSavings unavailable (pricing not published for one model).
Capability Signals
Scores are directional estimates from model metadata — not official benchmark results.
Llama 3.3 70B VersatileMMLU Signal (Reasoning)Mistral Large
69%
69%
Llama 3.3 70B VersatileHumanEval Signal (Coding)Mistral Large
69%
69%
Llama 3.3 70B VersatileAgentic Tooling SignalMistral Large
69%
69%
Llama 3.3 70B VersatileMultimodal SignalMistral Large
69%
69%
Capabilities Matrix
Feature highlights for architecture and production fit.
Llama 3.3 70B Versatile Strengths
- Balanced general-purpose profile for chat, extraction, and automation tasks.
Mistral Large Strengths
- Balanced general-purpose profile for chat, extraction, and automation tasks.
API Implementation
Quick start snippets for each provider style.
Groq (Python)
from openai import OpenAI
client = OpenAI()
response = client.chat.completions.create(
model="groq/llama-3.3-70b-versatile",
messages=[{"role": "user", "content": "Hello"}]
)
print(response.choices[0].message.content)Mistral AI (Python)
from openai import OpenAI
client = OpenAI()
response = client.chat.completions.create(
model="mistral-ai/mistral-large",
messages=[{"role": "user", "content": "Hello"}]
)
print(response.choices[0].message.content)Choose Llama 3.3 70B Versatile when...
- You want a balanced default for mixed chat and workflow automation workloads.
- You can measure quality with your own benchmark and prompt set.
Choose Mistral Large when...
- You want a balanced default for mixed chat and workflow automation workloads.
- You can measure quality with your own benchmark and prompt set.
Frequently Asked Questions
Practical checks before selecting a production model.
Which model is better for coding?
Coding preference depends on your stack and tool-calling needs. Compare the coding signal row, test with your repository tasks, and validate latency in your target region.
Which model is cheaper at scale?
Input and output token pricing can diverge by workload profile. Use the estimator with your monthly request count and token mix to get a realistic cost difference.
Are these official benchmark numbers?
Pricing is live from OpenRouter. Benchmark rows are ModelsAtlas metadata-based signals and should be treated as directional guidance, not official leaderboard scores.
Related Comparisons
Explore adjacent model matchups.