GPT · Mid-tier · 1,050K context window

GPT 5.6 Terra pricing for meeting notes

$0.0400 per call at 8,000 input / 2,000 output tokens.

Per call

$0.0400

10K calls/mo

$400

Cache savings

90% off input

Batch savings

50% off all

Calculate your GPT 5.6 Terra costs

Adjust token counts, volume, and discount toggles to model your meeting notes spend. Prices verified daily against provider pricing pages.

Configure your usage

8,000
100100K
2,000
5050K
10,000
1001M

Estimated cost

Monthly cost
$400
10,000 calls/month
Cost per call$0.04
Daily cost$13
Input rate$2.00/MTok
Output rate$12.00/MTok
Analyze your real spend

Quick start

Call GPT 5.6 Terra with the OpenAI Python SDK:

from openai import OpenAI

client = OpenAI()
response = client.chat.completions.create(
    model="gpt-5.6-terra",
    max_tokens=2000,
    messages=[{"role": "user", "content": "Your prompt here"}]
)
# Cost: ~$0.0400 per call at standard rates
# Input:  $2.00/MTok
# Output: $12.00/MTok

How GPT 5.6 Terra compares on cost

Per-call cost for all models scoring 50+ on meeting notes benchmarks. Hover for details.

Cheapest viable option: GPT 5.6 Luna at $0.004000/call (90% less, 84/100 quality).

What drives meeting notes cost

Transcripts are long and low-density (an hour of conversation is a lot of tokens carrying comparatively little information) while the notes that come back are short. That ratio makes this a strong fit for a fast-tier model plus the batch API: notes rarely need to exist within seconds of the meeting ending, and batch discounts apply to the whole request.

For GPT 5.6 Terra specifically, that means output tokens cost 6.0x more than input, at $12.00 vs $2.00 per MTok. At this use case’s 8,000/2,000 token split, output accounts for 60% of the $0.0400 per-call cost.

Complete GPT 5.6 Terra pricing breakdown

Standard token rates

Direction$/MTokTokens per call
Input$2.008,000
Output$12.002,000

Prompt caching: 90% off input tokens

Caching drops input cost from $2.00 to $0.20/MTok. For repeated system prompts, that saves $0.0144 per call.

Batch API: 50% off all tokens

Submit requests asynchronously and receive 50% off all token costs. This works best for offline pipelines where latency requirements are flexible.

Monthly cost projections

Monthly volumeCost per callStandard monthlyCached monthlyYou save with caching
10,000 calls$0.0400$400$256$144
50,000 calls$0.0400$2,000$1,280$720
100,000 calls$0.0400$4,000$2,560$1,440
500,000 calls$0.0400$20,000$12,800$7,200
1,000,000 calls$0.0400$40,000$25,600$14,400

GPT 5.6 Terra quality benchmarks for meeting notes

Use GPT 5.6 Terra for meeting notes

Scores 92/100 (rank #1 of 20). Strong pick for production meeting notes workloads.

Performance across all task types

GPT 5.6 Terra scores by task type. Meeting Notes highlighted.

Summarization *92Q&A92Extraction90Classification89Code Generation86Code Review84Reasoning82Creative Writing80
Task typeConfidence scoreRank out of 20
Summarization(current page)92/100#1
Q&A92/100#1
Extraction90/100#1
Classification89/100#1
Code Generation86/100#4
Code Review84/100#4
Reasoning82/100#4
Creative Writing80/100#5

Confidence scores are a third-party benchmark snapshot from week 29 of 2026. This snapshot is 8 weeks old, so treat the scores as directional and validate against your own evals.

Alternative models for meeting notes

12 models score 80+ on meeting notes benchmarks, sorted by input rate. Cheapest: GPT 5.6 Luna (90% less, 84/100 quality).

ModelProviderInput $/MTokOutput $/MTokQualityPer callvs GPT
GPT 5.6 LunaGPT$0.20$1.2084/100$0.00400090% cheaper
Gemini 3 FlashGemini$0.50$3.0083/100$0.010075% cheaper
Claude Haiku 4.5Claude$1.00$5.0082/100$0.018055% cheaper
Gemini 3.5 FlashGemini$1.50$9.0085/100$0.030025% cheaper
Claude Sonnet 5Claude$2.00$10.0091/100$0.036010% cheaper
Gemini 3.1 ProGemini$2.00$12.0087/100$0.0400same cost
GPT 5.4GPT$2.50$15.0091/100$0.050025% more
Claude Sonnet 4.6Claude$3.00$15.0090/100$0.054035% more
GPT 5.6 SolGPT$4.00$20.0090/100$0.072080% more
Claude Opus 4.8Claude$5.00$25.0088/100$0.0900125% more
GPT 5.5GPT$5.00$30.0089/100$0.1000150% more
Claude Fable 5Claude$10.00$50.0090/100$0.1800350% more

About GPT 5.6 Terra

Provider

GPT

Tier

Mid-tier

Context

1,050K tokens

Released

Jul 2026

Other models from GPT

ModelTierInput $/MTokOutput $/MTokContext
GPT 5.5Flagship$5.00$30.001,050K
GPT 5.4Mid-tier$2.50$15.001,050K
GPT 5.6 SolFlagship$4.00$20.001,050K
GPT 5.6 LunaFast / Budget$0.20$1.201,050K

You can compare GPT 5.6 Terra head-to-head against any other model on our model comparison pages, or track how pricing has changed over time on the pricing history tracker.

Frequently asked questions

How much does GPT 5.6 Terra cost for meeting notes per API call?

A typical meeting notes call using GPT 5.6 Terra costs about $0.0400 per call. This estimate uses 8,000 input tokens and 2,000 output tokens at standard rates. Standard rates are $2.00 per million input tokens and $12.00 per million output tokens.

Is GPT 5.6 Terra the best model for meeting notes?

GPT 5.6 Terra scores 92 out of 100 on meeting notes benchmarks overall. It ranks #1 across all 20 models in our cross-provider registry. It is the top-ranked model for this task type across all four providers. Confidence scores are a third-party benchmark snapshot from week 29 of 2026. This snapshot is 8 weeks old, so treat the scores as directional and validate against your own evals.

What is the cheapest model for meeting notes with good quality?

The most affordable model for meeting notes above 80/100 quality is GPT 5.6 Luna. It comes from GPT at $0.20 per million input tokens. Output costs $1.20 per million tokens with a quality score of 84/100. Switching from GPT 5.6 Terra to GPT 5.6 Luna saves about 90% per API call.

How can I reduce my GPT 5.6 Terra costs for meeting notes?

Three strategies lower GPT 5.6 Terra costs for this task type effectively. Prompt caching gives a 90% discount on input tokens when reusing system prompts. The batch API gives 50% off all tokens for asynchronous processing workloads. Prompt optimization reduces token counts through more concise instructions and context windows. Combining caching with batching brings your cost from $0.0400 to about $0.002000 per call.

How does GPT 5.6 Terra pricing compare to other GPT models?

GPT has 4 other models alongside GPT 5.6 Terra today: GPT 5.5 at $5.00/$30.00 per million tokens (flagship), GPT 5.4 at $2.50/$15.00 per million tokens (mid-tier), GPT 5.6 Sol at $4.00/$20.00 per million tokens (flagship), GPT 5.6 Luna at $0.20/$1.20 per million tokens (fast / budget). The right choice depends on whether your meeting notes workload prioritizes quality, cost, or speed.

What context window does GPT 5.6 Terra support?

GPT 5.6 Terra supports a context window of 1,050K tokens per API call. This sets the maximum combined length of your input prompt and generated response. For meeting notes, typical calls use 8,000 input and 2,000 output tokens. That is well within this limit, leaving room for longer prompts or multi-turn conversations.

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This calculator estimates costs based on published rates only. Connect your API usage to see where your money goes and which models drive your spend.