The AI arena is free today

Open Superagent

GPT-5.6 Sol vs GPT-6.1 Terra

GPT-5.6 Sol and GPT-6.1 Terra are closely matched at 52.7 and 47.5 on the LLM Stats Score. GPT-6.1 Terra is 5.6x cheaper per token.

OpenAI · OpenAI · Updated for 2026

Which is better?

GPT-5.6 Sol and GPT-6.1 Terra are closely matched on the overall LLM Stats Score at 52.7 and 47.5.

The models split the 6 individual benchmarks reported for both models evenly.

On price, GPT-6.1 Terra is roughly 5.6x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.

Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.

Choose GPT-5.6 Sol

  • you want predictable pricing at $5.00/M input and $30.00/M output

Choose GPT-6.1 Terra

  • cost matters — it's about 5.6x cheaper per token
  • you want the most recent training data — it shipped Oct 2026

At a glance

The differences that matter most.

Core performance indexes
52.7
#13
47.5
#36
51.5
#9
49.0
#19
42.4
#11
37.1
#30
39.0
#10
38.8
#12
Cost, coverage & limits
Benchmark wins
3 of 6
3 of 6
Input price
$5.00 / M
$1.00 / M
Output price
$30.00 / M
$5.00 / M
Context window
1,050,000
1,050,000

Capability indexes

Additional strengths measured across groups of related public benchmarks

1 shared
Index
GPT-5.6 Sol
GPT-6.1 Terra
29.3#22
33.3#5
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

45 reported for GPT-5.6 Sol · 8 for GPT-6.1 Terra

6 shared

GPT-5.6 Sol outperforms in 3 benchmarks (HealthBench, HealthBench Consensus, HealthBench Hard), while GPT-6.1 Terra is better at 3 benchmarks (Agents' Last Exam, HealthBench Professional, Terminal-Bench 4.0).

Both models are evenly matched across the benchmarks.

Thu Oct 29 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Pricing Analysis

Price comparison per million tokens

GPT-6.1 Terra costs less

For input processing, GPT-5.6 Sol ($5.00/1M tokens) is 5.0x more expensive than GPT-6.1 Terra ($1.00/1M tokens).

For output processing, GPT-5.6 Sol ($30.00/1M tokens) is 6.0x more expensive than GPT-6.1 Terra ($5.00/1M tokens).

In conclusion, GPT-5.6 Sol is more expensive than GPT-6.1 Terra.*

* Using a 3:1 ratio of input to output tokens

Lowest available price from all providers
Thu Oct 29 2026 • llm-stats.com
OpenAI
GPT-5.6 Sol
Input tokens$5.00
Output tokens$30.00
Best providerOpenAI
OpenAI
GPT-6.1 Terra
Input tokens$1.00
Output tokens$5.00
Best providerOpenAI
Notice missing or incorrect data?

Context Window

Maximum input and output token capacity

Both models have the same input context window of 1,050,000 tokens. Both models can generate responses up to 128,000 tokens.

OpenAI
GPT-5.6 Sol
Input1,050,000 tokens
Output128,000 tokens
OpenAI
GPT-6.1 Terra
Input1,050,000 tokens
Output128,000 tokens
Thu Oct 29 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Both GPT-5.6 Sol and GPT-6.1 Terra support multimodal inputs.

They are both capable of processing various types of data, offering versatility in application.

GPT-5.6 Sol

Text
Images
Audio
Video

GPT-6.1 Terra

Text
Images
Audio
Video

License

Usage and distribution terms

Both models are licensed under proprietary licenses.

Both models have usage restrictions defined by their respective organizations.

GPT-5.6 Sol

Proprietary

Closed source

GPT-6.1 Terra

Proprietary

Closed source

Release Timeline

When each model was launched

GPT-5.6 Sol was released on 2026-07-09, while GPT-6.1 Terra was released on 2026-10-26.

GPT-6.1 Terra is 4 months newer than GPT-5.6 Sol.

GPT-5.6 Sol

Jul 9, 2026

3 months ago

GPT-6.1 Terra

Oct 26, 2026

3 days ago

3mo newer

Knowledge Cutoff

When training data ends

GPT-5.6 Sol has a knowledge cutoff of 2026-02-16, while GPT-6.1 Terra has a cutoff of 2026-06-01.

GPT-6.1 Terra has more recent training data (up to 2026-06-01), making it potentially better informed about events through that date compared to GPT-5.6 Sol (2026-02-16).

GPT-5.6 Sol

Feb 2026

GPT-6.1 Terra

Jun 2026

4 mo newer

Provider Availability

GPT-5.6 Sol is available from OpenAI. GPT-6.1 Terra is available from OpenAI.

GPT-5.6 Sol

openai logo
OpenAI
Input Price:Input: $5.00/1MOutput Price:Output: $30.00/1M

GPT-6.1 Terra

openai logo
OpenAI
Input Price:Input: $1.00/1MOutput Price:Output: $5.00/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?

Judge for yourself.

Run your own prompts against GPT-5.6 Sol and GPT-6.1 Terra side-by-side, then vote on the output you prefer.

GPT-5.6 Sol
✓ Preferred
GPT-6.1 Terra
Open in Playground

FAQ

Common questions about GPT-5.6 Sol vs GPT-6.1 Terra.

Which is better, GPT-5.6 Sol or GPT-6.1 Terra?

GPT-5.6 Sol and GPT-6.1 Terra are closely matched on the LLM Stats Score at 52.7 and 47.5. GPT-5.6 Sol is made by OpenAI and GPT-6.1 Terra is made by OpenAI. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does GPT-5.6 Sol compare to GPT-6.1 Terra in benchmarks?

GPT-5.6 Sol scores Connectors: 100.0%, Capture-the-Flag Challenges (Internal): 96.7%, HealthBench Consensus: 95.5%, GPQA: 94.6%, MRCR v2 (8-needle): 91.5%. GPT-6.1 Terra scores HealthBench Consensus: 95.1%, HealthBench Professional: 62.7%, Agents' Last Exam: 60.0%, Terminal-Bench-Science 0.1: 58.3%, MentalHealthBench: 55.5%.

Is GPT-5.6 Sol cheaper than GPT-6.1 Terra?

GPT-6.1 Terra is 5.0x cheaper for input tokens. GPT-5.6 Sol costs $5.00/M input and $30.00/M output via openai. GPT-6.1 Terra costs $1.00/M input and $5.00/M output via openai.

What are the context window sizes for GPT-5.6 Sol and GPT-6.1 Terra?

GPT-5.6 Sol supports 1.1M tokens and GPT-6.1 Terra supports 1.1M tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between GPT-5.6 Sol and GPT-6.1 Terra?

Key differences include LLM Stats Score (52.7 vs 47.5), input pricing ($5.00 vs $1.00/M). See the full comparison above for benchmark-by-benchmark results.