API cost decision in 10 seconds

GPT-5.2 Chat vs Qwen3 Coder 30B A3B Instruct

Pick Qwen3 Coder 30B A3B Instruct 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 Qwen3 Coder 30B A3B Instruct when budget and context both matter.

On the standard 1M input plus 500K output workload, Qwen3 Coder 30B A3B Instruct is estimated at $0.21 vs $8.75 for GPT-5.2 Chat, saving $8.54 (97.7% lower).

Cost-first pickQwen3 Coder 30B A3B Instruct
Context-first pickQwen3 Coder 30B A3B Instruct
Sample savings$8.5497.7%
10x traffic gap$85.45

Qwen3 Coder 30B A3B Instruct is cheaper on the standard workload and also has the larger context window. At 10x that traffic, the same price gap is about $85.45. Use the calculator below to replace the sample workload with your own token volume.

Cost sensitivity

Workload Sensitivity

Same prices, different token mixes.

Qwen3 Coder 30B A3B Instruct stays cheaper across input-heavy, balanced, and output-heavy sample workloads.

Workload shapeToken mixBetter pickGPT-5.2 ChatQwen3 Coder 30B A3B Instruct
Input-heavy / RAG5M input + 500K outputQwen3 Coder 30B A3B Instruct$15.75$0.49
Balanced workload1M input + 1M outputQwen3 Coder 30B A3B Instruct$15.75$0.34
Output-heavy chatbot1M input + 5M outputQwen3 Coder 30B A3B Instruct$71.75$1.42
Cheaper input Qwen3 Coder 30B A3B Instruct $1.75 vs $0.07 / 1M

Qwen3 Coder 30B A3B Instruct is $1.68 cheaper per 1M input tokens (96% lower; 25x difference).

Cheaper output Qwen3 Coder 30B A3B Instruct $14 vs $0.27 / 1M

Qwen3 Coder 30B A3B Instruct is $13.73 cheaper per 1M output tokens (98.1% lower; 51.9x difference).

Larger context Qwen3 Coder 30B A3B Instruct 128K vs 160K

Qwen3 Coder 30B A3B Instruct has 32K more context (1.25x larger).

Sample workload Qwen3 Coder 30B A3B Instruct $8.75 vs $0.21

Qwen3 Coder 30B A3B Instruct is $8.54 cheaper on the standard workload (97.7% lower).

Estimate your workload cost

Your Workload Cost

Prices are normalized to USD per 1M tokens.
GPT-5.2 Chat Calculating… Estimated API cost
Qwen3 Coder 30B A3B Instruct 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 Coder 30B A3B Instruct has the lower input price; Qwen3 Coder 30B A3B Instruct has the lower output price; Qwen3 Coder 30B A3B Instruct offers the larger context window. For the 1M input plus 500K output sample, Qwen3 Coder 30B A3B Instruct is cheaper for the standard workload.

For a 1M input token plus 500K output token workload, the estimated API cost is $8.75 for GPT-5.2 Chat and $0.21 for Qwen3 Coder 30B A3B Instruct.

Best Fit

Choose GPT-5.2 Chat when its provider, model quality, latency, or availability is more important than the numeric price/context winner.

Choose Qwen3 Coder 30B A3B Instruct when you care most about lower input-token price, lower output-token price, and larger context window.

Decision Notes
  • On the standard 1M input plus 500K output workload, Qwen3 Coder 30B A3B Instruct is estimated at $0.21 vs $8.75 for GPT-5.2 Chat, saving $8.54 (97.7% lower).
  • Qwen3 Coder 30B A3B Instruct is $8.54 cheaper on the standard workload (97.7% lower).
  • Qwen3 Coder 30B A3B Instruct is $1.68 cheaper per 1M input tokens (96% lower; 25x difference).
  • Qwen3 Coder 30B A3B Instruct is $13.73 cheaper per 1M output tokens (98.1% lower; 51.9x difference).
  • Qwen3 Coder 30B A3B Instruct has 32K more context (1.25x larger).
Head-to-Head Specs
FeatureGPT-5.2 Chat
(OpenAI)
Qwen3 Coder 30B A3B Instruct
(Qwen)
Input Price
prompt tokens per 1M
$1.75$0.07
Completion Price
per 1M tokens
$14$0.27
Sample Workload Cost
1M input + 500K output
$8.75$0.21
Context Window128K160K
Release Date
Popularity#139#145

Use-Case Decision Matrix

Use caseBetter pickWhy
Budget-constrained productionQwen3 Coder 30B A3B InstructOn the standard 1M input plus 500K output workload, Qwen3 Coder 30B A3B Instruct is estimated at $0.21 vs $8.75 for GPT-5.2 Chat, saving $8.54 (97.7% lower).
High-volume input processingQwen3 Coder 30B A3B InstructLower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill.
Long responses and chatbotsQwen3 Coder 30B A3B InstructLower output-token price matters most when assistants generate many completion tokens.
RAG or long-document workQwen3 Coder 30B A3B InstructA larger context window leaves more room for retrieved passages, conversation history, or source files.

Related Alternatives

Same-provider lower-cost swaps
  • gpt-oss-120b (free) can replace GPT-5.2 Chat when lower sample workload cost matters most: $0.
  • gpt-oss-20b (free) can replace GPT-5.2 Chat when lower sample workload cost matters most: $0.
  • gpt-oss-20b can replace GPT-5.2 Chat when lower sample workload cost matters most: $0.1.
  • gpt-oss-120b can replace GPT-5.2 Chat when lower sample workload cost matters most: $0.13.
Larger context near this budget
  • Llama 4 Scout offers 10M context with $0.23 sample workload cost.
  • Grok 4.20 offers 2M context with $2.5 sample workload cost.
  • Grok 4.20 Multi-Agent offers 2M context with $5 sample workload cost.
  • GPT-5.4 offers 1.05M context with $10 sample workload cost.

Cheaper alternatives

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Larger context alternatives

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Provider catalogs

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

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OpenAI catalog

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

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Qwen catalog

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

Open Qwen models
GPT-5.2 Chat

GPT-5.2 Chat (AKA Instant) is the fast, lightweight member of the 5.2 family, optimized for low-latency chat while retaining strong general intelligence. It uses adaptive reasoning to selectively “think” on...

Qwen3 Coder 30B A3B Instruct

Qwen3-Coder-30B-A3B-Instruct is a 30.5B parameter Mixture-of-Experts (MoE) model with 128 experts (8 active per forward pass), designed for advanced code generation, repository-scale understanding, and agentic tool use. Built on the...