By the toolist.ai editors. Researched from public sources, not hands-on tested by toolist.ai. Updated October 27, 2026; prices checked October 21, 2026.

GPT-6.1 Terra vs Claude Sonnet 5.5

Verdict

Pick Claude Sonnet 5.5 for harder work and GPT-6.1 Terra for high-volume work where price comes first. Terra costs half as much per token ($1 and $5 per million against $2 and $10) and half as much for cached input ($0.05 against $0.10). Sonnet 5.5 scores higher on the Artificial Analysis Intelligence Index, 54 against 51 at max effort and 41 against 38 at each model's default effort, and it is faster, at 115.1 output tokens a second against 91.0 at each model's default effort.

Verdict based on published prices, limits and benchmarks, not on our own tests.

Choose GPT-6.1 Terra if

  • Cost matters most: Terra's $1 and $5 per million tokens against Sonnet's $2 and $10
  • You send product photos, technical drawings or application screens, which OpenAI says Terra is built for
  • You reuse long prompts: cached input costs $0.05 per million tokens against $0.10

Choose Claude Sonnet 5.5 if

  • You want the higher score at max effort: 54 against 51 on the Intelligence Index
  • You want faster answers: 115.1 against 91.0 output tokens a second at each model's default effort
  • You use the Claude apps, since Sonnet models are in them on every plan from Free to Enterprise

Price

Input costs 2 times as much on Claude Sonnet 5.5 as on GPT-6.1 Terra. Output costs 2 times as much on Claude Sonnet 5.5 as on GPT-6.1 Terra.

Per million tokensGPT-6.1 TerraClaude Sonnet 5.5
Input$1 source$2 source
Cached input$0.05 source$0.10 source
Output$5 source$10 source

GPT-6.1 Terra: Prompts over 272,000 input tokens cost twice the input and cache rates and 1.5 times the output rate for the whole request. Batch and Flex cost half; Fast mode costs double. Cache writes cost $1.25 per million tokens with 30-minute retention and $2.50 with 12-hour retention.

Claude Sonnet 5.5: Cache writes cost $2.50 per million tokens (5-minute cache) or $4 (1-hour cache). The Batch API costs half. There is no long-context surcharge and no fast mode.

Worked example: what a month costs

We priced three monthly workloads at the standard rates. The provider does not publish these figures.

WorkloadGPT-6.1 TerraClaude Sonnet 5.5
Support chatbot
100,000 replies, each 3,000 input and 400 output tokens, no caching (300M in, 40M out)
$500$1,000
Document Q&A
5,000 questions over the same 60,000-token document set (90% cache hits), 800 output tokens each (300M in, 4M out)
$63.50$127
Coding agent
200 tasks, each 1.5 million input tokens (90% cache hits) and 50,000 output tokens (300M in, 10M out)
$93.50$187

Price your own workload

ModelCost a month
GPT-6.1 Terra $75.00
Claude Sonnet 5.5 $150

Standard API prices, no batch or priority discounts. Cached input is billed at the cache-read price; cache-write charges are not included. Reasoning models bill their thinking as output tokens.

Limits and release dates

GPT-6.1 TerraClaude Sonnet 5.5
ReleasedOctober 26, 2026 sourceSeptember 28, 2026 source
Context window1,050,000 tokens source1,000,000 tokens source
Maximum output128,000 tokens source128,000 tokens source
Knowledge cutoffJune 1, 2026 sourceJune 2026 source
Input and outputText and images in; text out sourceText and images in; text out source
API model namegpt-6.1-terraclaude-sonnet-5-5

Benchmarks

Scores as published by the provider or measured by Artificial Analysis; higher is better. A dash means no score was published.

BenchmarkGPT-6.1 TerraClaude Sonnet 5.5
Artificial Analysis Intelligence Index
max effort
51.0 source54.0 source
Intelligence Index at everyday effort 38.0 (medium effort, the API default) source41.0 (high effort, the API default) source
Terminal-Bench 4.0 –64.0% (max effort) source
HLE-Diamond –53.0% (max effort) source
Terminal-Bench-Science 0.1 –53.0% (max effort) source
Output speed 91 tokens/s (medium effort, Artificial Analysis) source115.1 tokens/s (high effort, Artificial Analysis) source

Benchmark and speed data from Artificial Analysis where linked.

Read more

Sources