API cost decision in 10 seconds

Qwen3 VL 235B A22B Thinking vs Devstral 2 2512

Pick Devstral 2 2512 when budget and context both matter.

Page updated:  Data confirmed:  Prices normalized to USD per 1M tokens Sample workload: 1M input + 500K output

Budget verdict

Pick Devstral 2 2512 when budget and context both matter.

On the standard 1M input plus 500K output workload, Devstral 2 2512 is estimated at $1.4 vs $1.56 for Qwen3 VL 235B A22B Thinking, saving $0.16 (10.3% lower).

Cost-first pickDevstral 2 2512
Context-first pickDevstral 2 2512
Sample savings$0.1610.3%
10x traffic gap$1.6

Devstral 2 2512 is cheaper on the standard workload and also has the larger context window. At 10x that traffic, the same price gap is about $1.6. Use the calculator below to replace the sample workload with your own token volume.

Cost sensitivity

Workload Sensitivity

Same prices, different token mixes.

Cost winner changes by workload shape: input-heavy / RAG favors Qwen3 VL 235B A22B Thinking, balanced workload favors Devstral 2 2512, and output-heavy chatbot favors Devstral 2 2512.

Workload shapeToken mixBetter pickQwen3 VL 235B A22B ThinkingDevstral 2 2512
Input-heavy / RAG5M input + 500K outputQwen3 VL 235B A22B Thinking$2.6$3
Balanced workload1M input + 1M outputDevstral 2 2512$2.86$2.4
Output-heavy chatbot1M input + 5M outputDevstral 2 2512$13.26$10.4
Cheaper input Qwen3 VL 235B A22B Thinking $0.26 vs $0.4 / 1M

Qwen3 VL 235B A22B Thinking is $0.14 cheaper per 1M input tokens (35% lower; 1.54x difference).

Cheaper output Devstral 2 2512 $2.6 vs $2 / 1M

Devstral 2 2512 is $0.6 cheaper per 1M output tokens (23.1% lower; 1.3x difference).

Larger context Devstral 2 2512 131.07K vs 262.14K

Devstral 2 2512 has 131.07K more context (2x larger).

Sample workload Devstral 2 2512 $1.56 vs $1.4

Devstral 2 2512 is $0.16 cheaper on the standard workload (10.3% lower).

Estimate your workload cost

Your Workload Cost

Prices are normalized to USD per 1M tokens.
Qwen3 VL 235B A22B Thinking Calculating… Estimated API cost
Devstral 2 2512 Calculating… Estimated API cost
Cheaper for this workload Calculating… Difference: calculating…

This estimate uses normalized public API pricing per 1M tokens. It is a planning aid, not a billing quote. Verify provider pricing, limits, and terms before production use.

Quick Decision

Verdict

Qwen3 VL 235B A22B Thinking has the lower input price; Devstral 2 2512 has the lower output price; Devstral 2 2512 offers the larger context window. For the 1M input plus 500K output sample, Devstral 2 2512 is cheaper for the standard workload.

For a 1M input token plus 500K output token workload, the estimated API cost is $1.56 for Qwen3 VL 235B A22B Thinking and $1.4 for Devstral 2 2512.

Best Fit

Choose Qwen3 VL 235B A22B Thinking when you care most about lower input-token price.

Choose Devstral 2 2512 when you care most about lower output-token price, and larger context window.

Decision Notes
  • On the standard 1M input plus 500K output workload, Devstral 2 2512 is estimated at $1.4 vs $1.56 for Qwen3 VL 235B A22B Thinking, saving $0.16 (10.3% lower).
  • Devstral 2 2512 is $0.16 cheaper on the standard workload (10.3% lower).
  • Qwen3 VL 235B A22B Thinking is $0.14 cheaper per 1M input tokens (35% lower; 1.54x difference).
  • Devstral 2 2512 is $0.6 cheaper per 1M output tokens (23.1% lower; 1.3x difference).
  • Devstral 2 2512 has 131.07K more context (2x larger).
Head-to-Head Specs
FeatureQwen3 VL 235B A22B Thinking
(Qwen)		Devstral 2 2512
(Mistral)
Input Price
prompt tokens per 1M		$0.26$0.4
Completion Price
per 1M tokens		$2.6$2
Sample Workload Cost
1M input + 500K output		$1.56$1.4
Context Window131.07K262.14K
Release Date
Popularity#103#114

Use-Case Decision Matrix

Use caseBetter pickWhy
Budget-constrained productionDevstral 2 2512On the standard 1M input plus 500K output workload, Devstral 2 2512 is estimated at $1.4 vs $1.56 for Qwen3 VL 235B A22B Thinking, saving $0.16 (10.3% lower).
High-volume input processingQwen3 VL 235B A22B ThinkingLower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill.
Long responses and chatbotsDevstral 2 2512Lower output-token price matters most when assistants generate many completion tokens.
RAG or long-document workDevstral 2 2512A larger context window leaves more room for retrieved passages, conversation history, or source files.

Related Alternatives

Same-provider lower-cost swaps
  • Qwen3 Next 80B A3B Instruct (free) can replace Qwen3 VL 235B A22B Thinking when lower sample workload cost matters most: $0.
  • Qwen3 Coder 480B A35B (free) can replace Qwen3 VL 235B A22B Thinking when lower sample workload cost matters most: $0.
  • Qwen2.5 7B Instruct can replace Qwen3 VL 235B A22B Thinking when lower sample workload cost matters most: $0.09.
  • Qwen3.5-9B can replace Qwen3 VL 235B A22B Thinking when lower sample workload cost matters most: $0.11.
Larger context near this budget
  • Llama 4 Scout offers 10M context with $0.23 sample workload cost.
  • Owl Alpha offers 1.05M context with $0 sample workload cost.
  • MiMo-V2.5 offers 1.05M context with $0.28 sample workload cost.
  • DeepSeek V4 Flash offers 1.05M context with $0.2 sample workload cost.

Cheaper alternatives

Review low-cost models sorted by a standard 1M input plus 500K output workload.

Open cheapest models

Larger context alternatives

Find models with larger context windows for RAG, long documents, and codebase review.

Open largest context models

Provider catalogs

Compare models within provider hubs before choosing a final API vendor.

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Qwen catalog

Review all tracked Qwen models before deciding whether this matchup is the right shortlist.

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Mistral catalog

Check other Mistral models with comparable pricing, context, or release timing.

Open Mistral models
Qwen3 VL 235B A22B Thinking

Qwen3-VL-235B-A22B Thinking is a multimodal model that unifies strong text generation with visual understanding across images and video. The Thinking model is optimized for multimodal reasoning in STEM and math....

Devstral 2 2512

Devstral 2 is a state-of-the-art open-source model by Mistral AI specializing in agentic coding. It is a 123B-parameter dense transformer model supporting a 256K context window. Devstral 2 supports exploring...