API cost decision in 10 seconds

LongCat 2.0 vs GPT-5.6 Luna (batch)

Pick GPT-5.6 Luna (batch) 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 GPT-5.6 Luna (batch) when budget and context both matter.

On the standard 1M input plus 500K output workload, GPT-5.6 Luna (batch) is estimated at $0.4 vs $0.9 for LongCat 2.0, saving $0.5 (55.6% lower).

Cost-first pickGPT-5.6 Luna (batch)
Context-first pickGPT-5.6 Luna (batch)
Sample savings$0.555.6%
10x traffic gap$5

GPT-5.6 Luna (batch) is cheaper on the standard workload and also has the larger context window. At 10x that traffic, the same price gap is about $5. Use the calculator below to replace the sample workload with your own token volume.

Cost sensitivity

Workload Sensitivity

Same prices, different token mixes.

GPT-5.6 Luna (batch) stays cheaper across input-heavy, balanced, and output-heavy sample workloads.

Workload shapeToken mixBetter pickLongCat 2.0GPT-5.6 Luna (batch)
Input-heavy / RAG5M input + 500K outputGPT-5.6 Luna (batch)$2.1$0.8
Balanced workload1M input + 1M outputGPT-5.6 Luna (batch)$1.5$0.7
Output-heavy chatbot1M input + 5M outputGPT-5.6 Luna (batch)$6.3$3.1
Cheaper input GPT-5.6 Luna (batch) $0.3 vs $0.1 / 1M

GPT-5.6 Luna (batch) is $0.2 cheaper per 1M input tokens (66.7% lower; 3x difference).

Cheaper output GPT-5.6 Luna (batch) $1.2 vs $0.6 / 1M

GPT-5.6 Luna (batch) is $0.6 cheaper per 1M output tokens (50% lower; 2x difference).

Larger context GPT-5.6 Luna (batch) 1.05M vs 1.05M

GPT-5.6 Luna (batch) has 1.24K more context (1x larger).

Sample workload GPT-5.6 Luna (batch) $0.9 vs $0.4

GPT-5.6 Luna (batch) is $0.5 cheaper on the standard workload (55.6% lower).

Estimate your workload cost

Your Workload Cost

Prices are normalized to USD per 1M tokens.
LongCat 2.0 Calculating… Estimated API cost
GPT-5.6 Luna (batch) 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-5.6 Luna (batch) has the lower input price; GPT-5.6 Luna (batch) has the lower output price; GPT-5.6 Luna (batch) offers the larger context window. For the 1M input plus 500K output sample, GPT-5.6 Luna (batch) is cheaper for the standard workload.

For a 1M input token plus 500K output token workload, the estimated API cost is $0.9 for LongCat 2.0 and $0.4 for GPT-5.6 Luna (batch).

Best Fit

Choose LongCat 2.0 when its provider, model quality, latency, or availability is more important than the numeric price/context winner.

Choose GPT-5.6 Luna (batch) 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, GPT-5.6 Luna (batch) is estimated at $0.4 vs $0.9 for LongCat 2.0, saving $0.5 (55.6% lower).
  • GPT-5.6 Luna (batch) is $0.5 cheaper on the standard workload (55.6% lower).
  • GPT-5.6 Luna (batch) is $0.2 cheaper per 1M input tokens (66.7% lower; 3x difference).
  • GPT-5.6 Luna (batch) is $0.6 cheaper per 1M output tokens (50% lower; 2x difference).
  • GPT-5.6 Luna (batch) has 1.24K more context (1x larger).
Head-to-Head Specs
FeatureLongCat 2.0
(Meituan)		GPT-5.6 Luna (batch)
(OpenAI)
Input Price
prompt tokens per 1M		$0.3$0.1
Completion Price
per 1M tokens		$1.2$0.6
Sample Workload Cost
1M input + 500K output		$0.9$0.4
Context Window1.05M1.05M
Release Date

Use-Case Decision Matrix

Use caseBetter pickWhy
Budget-constrained productionGPT-5.6 Luna (batch)On the standard 1M input plus 500K output workload, GPT-5.6 Luna (batch) is estimated at $0.4 vs $0.9 for LongCat 2.0, saving $0.5 (55.6% lower).
High-volume input processingGPT-5.6 Luna (batch)Lower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill.
Long responses and chatbotsGPT-5.6 Luna (batch)Lower output-token price matters most when assistants generate many completion tokens.
RAG or long-document workGPT-5.6 Luna (batch)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-5.6 Luna (batch) when lower sample workload cost matters most: $0.
  • gpt-oss-20b (free) can replace GPT-5.6 Luna (batch) when lower sample workload cost matters most: $0.
  • gpt-oss-20b can replace GPT-5.6 Luna (batch) when lower sample workload cost matters most: $0.1.
  • gpt-oss-120b can replace GPT-5.6 Luna (batch) when lower sample workload cost matters most: $0.12.

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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Meituan catalog

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

Open Meituan models

OpenAI catalog

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

Open OpenAI models
LongCat 2.0

LongCat 2.0 is a sparse mixture-of-experts language model from Meituan, with 48B active parameters out of 1.6T total. It is suited for coding, repository-level changes, long-horizon problem solving, and agentic...

GPT-5.6 Luna (batch)

GPT-5.6 Luna is a fast, cost-efficient model in OpenAI's GPT-5.6 series. It is suited for high-volume, latency-sensitive tasks such as chat, classification, and lightweight agentic workflows, providing capable reasoning for...