API cost decision in 10 seconds

GPT-5 Nano vs Qwen3 Coder 480B A35B

Pick GPT-5 Nano for lower cost; pick Qwen3 Coder 480B A35B only if the larger context window matters more.

Page updated: 2026-05-26T15:08:08Z Data confirmed: 2026-05-26T18:08:02Z Prices normalized to USD per 1M tokens Sample workload: 1M input + 500K output

Budget verdict

Pick GPT-5 Nano for lower cost; pick Qwen3 Coder 480B A35B only if the larger context window matters more.

On the standard 1M input plus 500K output workload, GPT-5 Nano is estimated at $0.25 vs $1.12 for Qwen3 Coder 480B A35B, saving $0.87 (77.7% lower).

Cost-first pickGPT-5 Nano

Context-first pickQwen3 Coder 480B A35B

Sample savings$0.8777.7%

10x traffic gap$8.7

Qwen3 Coder 480B A35B has more context, but GPT-5 Nano saves $0.87 on the standard workload. At 10x that traffic, the same price gap is about $8.7. Use the calculator below to replace the sample workload with your own token volume.

Cost sensitivity

Workload Sensitivity

Same prices, different token mixes.

GPT-5 Nano stays cheaper across input-heavy, balanced, and output-heavy sample workloads.

Workload shape	Token mix	Better pick	GPT-5 Nano	Qwen3 Coder 480B A35B
Input-heavy / RAG	5M input + 500K output	GPT-5 Nano	$0.45	$2
Balanced workload	1M input + 1M output	GPT-5 Nano	$0.45	$2.02
Output-heavy chatbot	1M input + 5M output	GPT-5 Nano	$2.05	$9.22

Cheaper input GPT-5 Nano $0.05 vs $0.22 / 1M

GPT-5 Nano is $0.17 cheaper per 1M input tokens (77.3% lower; 4.4x difference).

Cheaper output GPT-5 Nano $0.4 vs $1.8 / 1M

GPT-5 Nano is $1.4 cheaper per 1M output tokens (77.8% lower; 4.5x difference).

Larger context Qwen3 Coder 480B A35B 400K vs 1.05M

Qwen3 Coder 480B A35B has 648.58K more context (2.62x larger).

Sample workload GPT-5 Nano $0.25 vs $1.12

GPT-5 Nano is $0.87 cheaper on the standard workload (77.7% lower).

Estimate your workload cost

Your Workload Cost

Prices are normalized to USD per 1M tokens.

Monthly input tokens Monthly output tokens

GPT-5 Nano Calculating… Estimated API cost

Qwen3 Coder 480B A35B 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

GPT-5 Nano has the lower input price; GPT-5 Nano has the lower output price; Qwen3 Coder 480B A35B offers the larger context window. For the 1M input plus 500K output sample, GPT-5 Nano is cheaper for the standard workload.

For a 1M input token plus 500K output token workload, the estimated API cost is $0.25 for GPT-5 Nano and $1.12 for Qwen3 Coder 480B A35B.

Best Fit

Choose GPT-5 Nano when you care most about lower input-token price, and lower output-token price.

Choose Qwen3 Coder 480B A35B when you care most about larger context window.

Decision Notes

On the standard 1M input plus 500K output workload, GPT-5 Nano is estimated at $0.25 vs $1.12 for Qwen3 Coder 480B A35B, saving $0.87 (77.7% lower).
GPT-5 Nano is $0.87 cheaper on the standard workload (77.7% lower).
GPT-5 Nano is $0.17 cheaper per 1M input tokens (77.3% lower; 4.4x difference).
GPT-5 Nano is $1.4 cheaper per 1M output tokens (77.8% lower; 4.5x difference).
Qwen3 Coder 480B A35B has 648.58K more context (2.62x larger).

Head-to-Head Specs

Feature	GPT-5 Nano (OpenAI)	Qwen3 Coder 480B A35B (Qwen)
Input Price prompt tokens per 1M	$0.05	$0.22
Completion Price per 1M tokens	$0.4	$1.8
Sample Workload Cost 1M input + 500K output	$0.25	$1.12
Context Window	400K	1.05M
Release Date	2025-08-07	2025-07-23
Popularity	#68	#97

Use-Case Decision Matrix

Use case	Better pick	Why
Budget-constrained production	GPT-5 Nano	On the standard 1M input plus 500K output workload, GPT-5 Nano is estimated at $0.25 vs $1.12 for Qwen3 Coder 480B A35B, saving $0.87 (77.7% lower).
High-volume input processing	GPT-5 Nano	Lower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill.
Long responses and chatbots	GPT-5 Nano	Lower output-token price matters most when assistants generate many completion tokens.
RAG or long-document work	Qwen3 Coder 480B A35B	A 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 Nano when lower sample workload cost matters most: $0.
gpt-oss-20b (free) can replace GPT-5 Nano when lower sample workload cost matters most: $0.
gpt-oss-20b can replace GPT-5 Nano when lower sample workload cost matters most: $0.1.
gpt-oss-120b can replace GPT-5 Nano 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.
Owl Alpha offers 1.05M context with $0 sample workload cost.

Popular competitors

DeepSeek V4 Flash · DeepSeek · #1
Hy3 preview · Tencent · #2
Claude Opus 4.7 · Anthropic · #3
Claude Sonnet 4.6 · Anthropic · #4

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

OpenAI catalog

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

Open OpenAI models

Qwen catalog

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

Open Qwen models

GPT-5 Nano

GPT-5-Nano is the smallest and fastest variant in the GPT-5 system, optimized for developer tools, rapid interactions, and ultra-low latency environments. While limited in reasoning depth compared to its larger...

Qwen3 Coder 480B A35B

Qwen3-Coder-480B-A35B-Instruct is a Mixture-of-Experts (MoE) code generation model developed by the Qwen team. It is optimized for agentic coding tasks such as function calling, tool use, and long-context reasoning over...