API cost decision in 10 seconds

GPT-5.6 Terra Pro (batch) vs Gemini 3.5 Flash

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

On the standard 1M input plus 500K output workload, GPT-5.6 Terra Pro (batch) is estimated at $4 vs $6 for Gemini 3.5 Flash, saving $2 (33.3% lower).

Cost-first pickGPT-5.6 Terra Pro (batch)
Context-first pickGPT-5.6 Terra Pro (batch)
Sample savings$233.3%
10x traffic gap$20

GPT-5.6 Terra Pro (batch) is cheaper on the standard workload and also has the larger context window. At 10x that traffic, the same price gap is about $20. 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 Terra Pro (batch) stays cheaper across input-heavy, balanced, and output-heavy sample workloads.

Workload shapeToken mixBetter pickGPT-5.6 Terra Pro (batch)Gemini 3.5 Flash
Input-heavy / RAG5M input + 500K outputGPT-5.6 Terra Pro (batch)$8$12
Balanced workload1M input + 1M outputGPT-5.6 Terra Pro (batch)$7$10.5
Output-heavy chatbot1M input + 5M outputGPT-5.6 Terra Pro (batch)$31$46.5
Cheaper input GPT-5.6 Terra Pro (batch) $1 vs $1.5 / 1M

GPT-5.6 Terra Pro (batch) is $0.5 cheaper per 1M input tokens (33.3% lower; 1.5x difference).

Cheaper output GPT-5.6 Terra Pro (batch) $6 vs $9 / 1M

GPT-5.6 Terra Pro (batch) is $3 cheaper per 1M output tokens (33.3% lower; 1.5x difference).

Larger context GPT-5.6 Terra Pro (batch) 1.05M vs 1.05M

GPT-5.6 Terra Pro (batch) has 1.42K more context (1x larger).

Sample workload GPT-5.6 Terra Pro (batch) $4 vs $6

GPT-5.6 Terra Pro (batch) is $2 cheaper on the standard workload (33.3% lower).

Estimate your workload cost

Your Workload Cost

Prices are normalized to USD per 1M tokens.
GPT-5.6 Terra Pro (batch) Calculating… Estimated API cost
Gemini 3.5 Flash 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 Terra Pro (batch) has the lower input price; GPT-5.6 Terra Pro (batch) has the lower output price; GPT-5.6 Terra Pro (batch) offers the larger context window. For the 1M input plus 500K output sample, GPT-5.6 Terra Pro (batch) is cheaper for the standard workload.

For a 1M input token plus 500K output token workload, the estimated API cost is $4 for GPT-5.6 Terra Pro (batch) and $6 for Gemini 3.5 Flash.

Best Fit

Choose GPT-5.6 Terra Pro (batch) when you care most about lower input-token price, lower output-token price, and larger context window.

Choose Gemini 3.5 Flash when its provider, model quality, latency, or availability is more important than the numeric price/context winner.

Decision Notes
  • On the standard 1M input plus 500K output workload, GPT-5.6 Terra Pro (batch) is estimated at $4 vs $6 for Gemini 3.5 Flash, saving $2 (33.3% lower).
  • GPT-5.6 Terra Pro (batch) is $2 cheaper on the standard workload (33.3% lower).
  • GPT-5.6 Terra Pro (batch) is $0.5 cheaper per 1M input tokens (33.3% lower; 1.5x difference).
  • GPT-5.6 Terra Pro (batch) is $3 cheaper per 1M output tokens (33.3% lower; 1.5x difference).
  • GPT-5.6 Terra Pro (batch) has 1.42K more context (1x larger).
Head-to-Head Specs
FeatureGPT-5.6 Terra Pro (batch)
(OpenAI)		Gemini 3.5 Flash
(Google)
Input Price
prompt tokens per 1M		$1$1.5
Completion Price
per 1M tokens		$6$9
Sample Workload Cost
1M input + 500K output		$4$6
Context Window1.05M1.05M
Release Date

Use-Case Decision Matrix

Use caseBetter pickWhy
Budget-constrained productionGPT-5.6 Terra Pro (batch)On the standard 1M input plus 500K output workload, GPT-5.6 Terra Pro (batch) is estimated at $4 vs $6 for Gemini 3.5 Flash, saving $2 (33.3% lower).
High-volume input processingGPT-5.6 Terra Pro (batch)Lower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill.
Long responses and chatbotsGPT-5.6 Terra Pro (batch)Lower output-token price matters most when assistants generate many completion tokens.
RAG or long-document workGPT-5.6 Terra Pro (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 Terra Pro (batch) when lower sample workload cost matters most: $0.
  • gpt-oss-20b (free) can replace GPT-5.6 Terra Pro (batch) when lower sample workload cost matters most: $0.
  • gpt-oss-20b can replace GPT-5.6 Terra Pro (batch) when lower sample workload cost matters most: $0.1.
  • gpt-oss-120b can replace GPT-5.6 Terra Pro (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.

Open provider hubs

OpenAI catalog

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

Open OpenAI models

Google catalog

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

Open Google models
GPT-5.6 Terra Pro (batch)

GPT-5.6 Terra Pro is the same underlying model as [GPT-5.6 Terra](https://openrouter.ai/openai/gpt-5.6-terra), served with `reasoning.mode` set to `pro` for higher-quality responses on complex tasks. Learn more in OpenAI's docs: https://developers.openai.com/api/docs/guides/reasoning#reasoning-mode

Gemini 3.5 Flash

Gemini 3.5 Flash is Google's high-efficiency multimodal model, bringing near-Pro level coding and reasoning at Flash-tier cost and speed. It is highly optimized for coding proficiency and parallel agentic execution...