GPT-6.1 Terra vs Qwen3.8 Flash
GPT-6.1 Terra and Qwen3.8 Flash are closely matched at 47.6 and 47.8 on the LLM Stats Score. Qwen3.8 Flash is 8.7x cheaper per token.
OpenAI · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
GPT-6.1 Terra and Qwen3.8 Flash are closely matched on the overall LLM Stats Score at 47.6 and 47.8.
In the 1 individual benchmarks reported for both models, GPT-6.1 Terra wins 1; this is a narrower head-to-head signal than the composite indexes.
On price, Qwen3.8 Flash is roughly 8.7x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
GPT-6.1 Terra also accepts a larger context window (1,050,000 input tokens), making it the stronger choice for long documents and large codebases.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose GPT-6.1 Terra
- your work emphasizes agents — it leads those capability indexes
- you value its reported benchmark strengths — it wins 1 of 1 exact shared results
- you process long inputs — it offers a 1,050,000 token context window
- you want the most recent training data — it shipped Oct 2026
Choose Qwen3.8 Flash
- cost matters — it's about 8.7x cheaper per token
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
9 reported for GPT-6.1 Terra · 22 for Qwen3.8 Flash
GPT-6.1 Terra outperforms in 1 benchmarks (Agents' Last Exam), while Qwen3.8 Flash is better at 0 benchmarks.
GPT-6.1 Terra significantly outperforms across most benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, GPT-6.1 Terra ($1.00/1M tokens) is 6.7x more expensive than Qwen3.8 Flash ($0.15/1M tokens).
For output processing, GPT-6.1 Terra ($5.00/1M tokens) is 10.6x more expensive than Qwen3.8 Flash ($0.47/1M tokens).
In conclusion, GPT-6.1 Terra is more expensive than Qwen3.8 Flash.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
GPT-6.1 Terra accepts 1,050,000 input tokens compared to Qwen3.8 Flash's 1,000,000 tokens. Qwen3.8 Flash can generate longer responses up to 131,072 tokens, while GPT-6.1 Terra is limited to 128,000 tokens.
Input capabilities
Documented input modalities across available providers
Both GPT-6.1 Terra and Qwen3.8 Flash support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
GPT-6.1 Terra
Qwen3.8 Flash
License
Usage and distribution terms
Both models are licensed under proprietary licenses.
Both models have usage restrictions defined by their respective organizations.
Proprietary
Closed source
Proprietary
Closed source
Release Timeline
When each model was launched
GPT-6.1 Terra was released on 2026-10-26, while Qwen3.8 Flash was released on 2026-08-26.
GPT-6.1 Terra is 2 months newer than Qwen3.8 Flash.
Oct 26, 2026
1 weeks ago
2mo newerAug 26, 2026
2 months ago
Knowledge Cutoff
When training data ends
GPT-6.1 Terra has a documented knowledge cutoff of 2026-06-01, while Qwen3.8 Flash's cutoff date is not specified.
We can confirm GPT-6.1 Terra's training data extends to 2026-06-01, but cannot make a direct comparison without Qwen3.8 Flash's cutoff date.
Jun 2026
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Provider Availability
GPT-6.1 Terra is available from OpenAI. Qwen3.8 Flash is available from Novita.
GPT-6.1 Terra
Qwen3.8 Flash
Outputs Comparison
Judge for yourself.
Run your own prompts against GPT-6.1 Terra and Qwen3.8 Flash side-by-side, then vote on the output you prefer.
FAQ
Common questions about GPT-6.1 Terra vs Qwen3.8 Flash.