API cost decision in 10 seconds

NewCoBuddy (free) vs Qwen3 30B A3B Instruct 2507

Pick CoBuddy (free) for lower cost; pick Qwen3 30B A3B Instruct 2507 only if the larger context window matters more.

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

Budget verdict

Pick CoBuddy (free) for lower cost; pick Qwen3 30B A3B Instruct 2507 only if the larger context window matters more.

On the standard 1M input plus 500K output workload, CoBuddy (free) is estimated at $0 vs $0.24 for Qwen3 30B A3B Instruct 2507, saving $0.24 (100% lower).

Cost-first pickCoBuddy (free)
Context-first pickQwen3 30B A3B Instruct 2507
Sample savings$0.24100%
10x traffic gap$2.4

Qwen3 30B A3B Instruct 2507 has more context, but CoBuddy (free) saves $0.24 on the standard workload. At 10x that traffic, the same price gap is about $2.4. Use the calculator below to replace the sample workload with your own token volume.

Cost sensitivity

Workload Sensitivity

Same prices, different token mixes.

CoBuddy (free) stays cheaper across input-heavy, balanced, and output-heavy sample workloads.

Workload shapeToken mixBetter pickCoBuddy (free)Qwen3 30B A3B Instruct 2507
Input-heavy / RAG5M input + 500K outputCoBuddy (free)$0$0.6
Balanced workload1M input + 1M outputCoBuddy (free)$0$0.39
Output-heavy chatbot1M input + 5M outputCoBuddy (free)$0$1.59
Cheaper input CoBuddy (free) $0 vs $0.09 / 1M

CoBuddy (free) is free for input tokens while Qwen3 30B A3B Instruct 2507 costs $0.09 per 1M tokens.

Cheaper output CoBuddy (free) $0 vs $0.3 / 1M

CoBuddy (free) is free for output tokens while Qwen3 30B A3B Instruct 2507 costs $0.3 per 1M tokens.

Larger context Qwen3 30B A3B Instruct 2507 131.07K vs 262.14K

Qwen3 30B A3B Instruct 2507 has 131.07K more context (2x larger).

Sample workload CoBuddy (free) $0 vs $0.24

CoBuddy (free) is free for the standard workload while the other model is estimated at $0.24.

Estimate your workload cost

Your Workload Cost

Prices are normalized to USD per 1M tokens.
CoBuddy (free) Calculating… Estimated API cost
Qwen3 30B A3B Instruct 2507 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

CoBuddy (free) has the lower input price; CoBuddy (free) has the lower output price; Qwen3 30B A3B Instruct 2507 offers the larger context window. For the 1M input plus 500K output sample, CoBuddy (free) is cheaper for the standard workload.

For a 1M input token plus 500K output token workload, the estimated API cost is $0 for CoBuddy (free) and $0.24 for Qwen3 30B A3B Instruct 2507.

Best Fit

Choose CoBuddy (free) when you care most about lower input-token price, and lower output-token price.

Choose Qwen3 30B A3B Instruct 2507 when you care most about larger context window.

Decision Notes
  • On the standard 1M input plus 500K output workload, CoBuddy (free) is estimated at $0 vs $0.24 for Qwen3 30B A3B Instruct 2507, saving $0.24 (100% lower).
  • CoBuddy (free) is free for the standard workload while the other model is estimated at $0.24.
  • CoBuddy (free) is free for input tokens while Qwen3 30B A3B Instruct 2507 costs $0.09 per 1M tokens.
  • CoBuddy (free) is free for output tokens while Qwen3 30B A3B Instruct 2507 costs $0.3 per 1M tokens.
  • Qwen3 30B A3B Instruct 2507 has 131.07K more context (2x larger).
Head-to-Head Specs
FeatureNewCoBuddy (free)
(Baidu Qianfan)
Qwen3 30B A3B Instruct 2507
(Qwen)
Input Price
prompt tokens per 1M
$0$0.09
Completion Price
per 1M tokens
$0$0.3
Sample Workload Cost
1M input + 500K output
$0$0.24
Context Window131.07K262.14K
Release Date
Popularity#83#110

Use-Case Decision Matrix

Use caseBetter pickWhy
Budget-constrained productionCoBuddy (free)On the standard 1M input plus 500K output workload, CoBuddy (free) is estimated at $0 vs $0.24 for Qwen3 30B A3B Instruct 2507, saving $0.24 (100% lower).
High-volume input processingCoBuddy (free)Lower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill.
Long responses and chatbotsCoBuddy (free)Lower output-token price matters most when assistants generate many completion tokens.
RAG or long-document workQwen3 30B A3B Instruct 2507A 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 30B A3B Instruct 2507 when lower sample workload cost matters most: $0.
  • Qwen3 Coder 480B A35B (free) can replace Qwen3 30B A3B Instruct 2507 when lower sample workload cost matters most: $0.
  • Qwen2.5 7B Instruct can replace Qwen3 30B A3B Instruct 2507 when lower sample workload cost matters most: $0.09.
  • Qwen3.5-9B can replace Qwen3 30B A3B Instruct 2507 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.
  • DeepSeek V4 Flash offers 1.05M context with $0.2 sample workload cost.
  • MiMo-V2.5 offers 1.05M context with $0.28 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.

Open provider hubs

Baidu Qianfan catalog

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

Open Baidu Qianfan models

Qwen catalog

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

Open Qwen models
CoBuddy (free)

CoBuddy is a code generation model from Baidu, optimized for coding tasks and AI Agent workflows. It features high inference throughput and low end-to-end latency, with native support for tool...

Qwen3 30B A3B Instruct 2507

Qwen3-30B-A3B-Instruct-2507 is a 30.5B-parameter mixture-of-experts language model from Qwen, with 3.3B active parameters per inference. It operates in non-thinking mode and is designed for high-quality instruction following, multilingual understanding, and...