Codestral vs Llama 3.3 70B
Codestral vs Llama 3.3 70B: Codestral is cheaper for input-heavy usage ($0.30/M vs $0.88/M input tokens), while Llama 3.3 70B is better for long-context tasks (131,072 tokens).
Direct answer: choose Codestral for lower token spend and choose Llama 3.3 70B when your workload needs longer context.
Compare input and output token pricing, context windows, and monthly cost estimates on one page so you can pick the cheaper model fast.
Cost Comparison (1000 input + 500 output tokens, 100 requests/day)
Codestral
Llama 3.3 70B
Cost Differences
Llama 3.3 70B costs more than Codestral
Quick Recommendation
Winner for direct API pricing: Codestral. At the default workload, Codestral saves about $1.71/month ($20.805/year) versus Llama 3.3 70B.
Feature Comparison
| Feature | Codestral | Llama 3.3 70B |
|---|---|---|
| Provider | Mistral AI | Meta (via Together AI) |
| Input Price | $0.30/1M tokens | $0.88/1M tokens |
| Output Price | $0.90/1M tokens | $0.88/1M tokens |
| Context Window | 128,000 tokens | 131,072 tokens |
| Max Output | 32,768 tokens | 4,096 tokens |
| Category | balanced | standard |
| Capabilities | textcode | textcode |
| Release Date | 7/30/2025 | 12/6/2024 |
Codestral vs Llama 3.3 70B: Which Should You Choose?
Choosing between Codestral and Llama 3.3 70B depends on your priorities: cost efficiency, context length, or raw capability. Codestral is the more affordable option at $0.30/1M input tokens — 66% cheaper than Llama 3.3 70B. Meanwhile, Llama 3.3 70B offers a significantly larger context window at 131,072 tokens vs 128,000 for Codestral.
These models come from different providers — Mistral AI and Meta (via Together AI) — which means different API ecosystems, SDKs, rate limits, and terms of service. If you're already integrated with Mistral AI, switching to Meta (via Together AI)involves migration effort beyond just pricing. Factor in your existing infrastructure when deciding.
These models target different tiers: Codestral is a balanced model while Llama 3.3 70B is standard. This means they're optimized for different workloads. Llama 3.3 70B targets more demanding workloads, while Codestral provides a cost-effective option for everyday tasks.
Output costs matter too. Codestral charges $0.90/1M output tokens vs $0.88 for Llama 3.3 70B. For generation-heavy workloads (content creation, code generation, summarization), output pricing often dominates your bill. Codestral has the edge here at $0.90/1M output tokens.
Best Use Cases
Choose Codestral when:
- • Budget is a primary concern
- • You need longer outputs (up to 32,768 tokens)
- • You're already using Mistral AI's API ecosystem
Choose Llama 3.3 70B when:
- • You need a larger context window (131,072 tokens)
- • You're already using Meta (via Together AI)'s API ecosystem
Pros and Caveats at a Glance
Codestral
- • Input pricing: $0.30/M tokens
- • Output pricing: $0.90/M tokens
- • Context window: 128,000 tokens
- • Max output: 32,768 tokens
Watch out for
- • Higher output cost than Llama 3.3 70B
- • Smaller context window than Llama 3.3 70B
Llama 3.3 70B
- • Input pricing: $0.88/M tokens
- • Output pricing: $0.88/M tokens
- • Context window: 131,072 tokens
- • Max output: 4,096 tokens
Watch out for
- • Higher input cost than Codestral
Try Different Scenarios
Use the calculator below to see how costs change with different usage patterns
Codestral (Mistral AI)
Llama 3.3 70B (Meta (via Together AI))
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Sign Up for Meta (via Together AI) →Frequently Asked Questions
Which is cheaper, Codestral or Llama 3.3 70B?▼
What is the context window difference between Codestral and Llama 3.3 70B?▼
Which model is better for AI Chatbot?▼
Which model has better overall pricing for heavy usage?▼
Where can I compare Mistral AI and Meta (via Together AI) API pricing beyond this model matchup?▼
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