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Devstral 2 vs Llama 4 Maverick

Compare Mistral AI and Meta (via Together AI) AI models

Mistral AI
Devstral 2
vs
Meta (via Together AI)
Llama 4 Maverick

Cost Comparison (1000 input + 500 output tokens, 100 requests/day)

Devstral 2

Per Request:$0.001400
Daily:$0.14
Monthly:$4.20
Yearly:$51.10

Llama 4 Maverick

Per Request:$0.000695
Daily:$0.0695
Monthly:$2.085
Yearly:$25.3675

Cost Differences

$0.000705
Per Request
$0.0705
Daily
$2.115
Monthly
$25.7325
Yearly

Llama 4 Maverick costs less than Devstral 2

Feature Comparison

FeatureDevstral 2Llama 4 Maverick
ProviderMistral AIMeta (via Together AI)
Input Price$0.40/1M tokens$0.27/1M tokens
Output Price$2.00/1M tokens$0.85/1M tokens
Context Window262,144 tokens1,000,000 tokens
Max Output32,768 tokens65,536 tokens
Categoryefficientflagship
Capabilities
textcode
textvisioncode
Release Date12/9/20254/5/2025

Devstral 2 vs Llama 4 Maverick: Which Should You Choose?

Choosing between Devstral 2 and Llama 4 Maverick depends on your priorities: cost efficiency, context length, or raw capability. Llama 4 Maverick is the more affordable option at $0.27/1M input tokens32% cheaper than Devstral 2. Meanwhile, Llama 4 Maverick offers a significantly larger context window at 1,000,000 tokens vs 262,144 for Devstral 2.

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: Devstral 2 is a efficient model while Llama 4 Maverick is flagship. This means they're optimized for different workloads. Llama 4 Maverick targets more demanding workloads, while Devstral 2 provides a cost-effective option for everyday tasks.

Output costs matter too. Devstral 2 charges $2.00/1M output tokens vs $0.85 for Llama 4 Maverick. For generation-heavy workloads (content creation, code generation, summarization), output pricing often dominates your bill. Llama 4 Maverick has the edge here at $0.85/1M output tokens.

Multimodal capabilities: Llama 4 Maverick supports vision (image inputs) while Devstral 2 is text-only. If your application needs image understanding, this narrows your choice.

Best Use Cases

Choose Devstral 2 when:

  • • You're already using Mistral AI's API ecosystem
  • • You're running high-volume, latency-sensitive workloads

Choose Llama 4 Maverick when:

  • • Budget is a primary concern
  • • You need a larger context window (1,000,000 tokens)
  • • You need more capabilities (vision)
  • • You need longer outputs (up to 65,536 tokens)
  • • You're already using Meta (via Together AI)'s API ecosystem

Try Different Scenarios

Use the calculator below to see how costs change with different usage patterns

Devstral 2 (Mistral AI)

Llama 4 Maverick (Meta (via Together AI))

Start using Devstral 2 today

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Start using Llama 4 Maverick today

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Frequently Asked Questions

Which is cheaper, Devstral 2 or Llama 4 Maverick?
Llama 4 Maverick is cheaper for input tokens at $0.27 per million tokens vs $0.40 for Devstral 2 — that's 32% savings on input costs.
What is the context window difference between Devstral 2 and Llama 4 Maverick?
Devstral 2 supports 262,144 tokens while Llama 4 Maverick supports 1,000,000 tokens — a difference of 737,856 tokens in favor of Llama 4 Maverick.
Which model is better for AI Chatbot?
Both models support text. For ai chatbot, Llama 4 Maverick is the lower-cost option, while Llama 4 Maverick offers a larger context window (1,000,000 vs 262,144 tokens). Choose Llama 4 Maverick for budget sensitivity or Llama 4 Maverick for longer context tasks.
Which model has better overall pricing for heavy usage?
At 100 requests/day with 1,000 input and 500 output tokens each, Devstral 2 costs about $4.20/month and Llama 4 Maverick costs about $2.085/month. Overall, Llama 4 Maverick has lower combined input + output rates ($0.27 in, $0.85 out) vs Devstral 2.

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