API cost decision in 10 seconds

New🔥Ring-2.6-1T (free) vs 🔥gpt-oss-120b

Pick Ring-2.6-1T (free) when budget and context both matter.

Pricing data updated:  Prices normalized to USD per 1M tokens Sample workload: 1M input + 500K output

Budget verdict

Pick Ring-2.6-1T (free) when budget and context both matter.

On the standard 1M input plus 500K output workload, Ring-2.6-1T (free) is estimated at $0 vs $0.13 for gpt-oss-120b, saving $0.13 (100% lower).

Cost-first pickRing-2.6-1T (free)
Context-first pickRing-2.6-1T (free)
Sample savings$0.13100%
10x traffic gap$1.29

Ring-2.6-1T (free) is cheaper on the standard workload and also has the larger context window. At 10x that traffic, the same price gap is about $1.29. Use the calculator below to replace the sample workload with your own token volume.

Cheaper input Ring-2.6-1T (free) $0 vs $0.039 / 1M

Ring-2.6-1T (free) is free for input tokens while gpt-oss-120b costs $0.04 per 1M tokens.

Cheaper output Ring-2.6-1T (free) $0 vs $0.18 / 1M

Ring-2.6-1T (free) is free for output tokens while gpt-oss-120b costs $0.18 per 1M tokens.

Larger context Ring-2.6-1T (free) 262.14K vs 131.07K

Ring-2.6-1T (free) has 131.07K more context (2x larger).

Sample workload Ring-2.6-1T (free) $0 vs $0.13

Ring-2.6-1T (free) is free for the standard workload while the other model is estimated at $0.13.

Estimate your workload cost

Your Workload Cost

Prices are normalized to USD per 1M tokens.
Ring-2.6-1T (free) Calculating… Estimated API cost
gpt-oss-120b 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

Ring-2.6-1T (free) has the lower input price; Ring-2.6-1T (free) has the lower output price; Ring-2.6-1T (free) offers the larger context window. For the 1M input plus 500K output sample, Ring-2.6-1T (free) is cheaper for the standard workload.

For a 1M input token plus 500K output token workload, the estimated API cost is $0 for Ring-2.6-1T (free) and $0.13 for gpt-oss-120b.

Best Fit

Choose Ring-2.6-1T (free) when you care most about lower input-token price, lower output-token price, and larger context window.

Choose gpt-oss-120b 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, Ring-2.6-1T (free) is estimated at $0 vs $0.13 for gpt-oss-120b, saving $0.13 (100% lower).
  • Ring-2.6-1T (free) is free for the standard workload while the other model is estimated at $0.13.
  • Ring-2.6-1T (free) is free for input tokens while gpt-oss-120b costs $0.04 per 1M tokens.
  • Ring-2.6-1T (free) is free for output tokens while gpt-oss-120b costs $0.18 per 1M tokens.
  • Ring-2.6-1T (free) has 131.07K more context (2x larger).
Head-to-Head Specs
FeatureNew🔥Ring-2.6-1T (free)
(inclusionAI)
🔥gpt-oss-120b
(OpenAI)
Input Price
prompt tokens per 1M
$0$0.039
Completion Price
per 1M tokens
$0$0.18
Sample Workload Cost
1M input + 500K output
$0$0.13
Context Window262.14K131.07K
Release Date2026-05-082025-08-05
Popularity Rank
current rank
#10#20

Use-Case Decision Matrix

Use caseBetter pickWhy
Budget-constrained productionRing-2.6-1T (free)On the standard 1M input plus 500K output workload, Ring-2.6-1T (free) is estimated at $0 vs $0.13 for gpt-oss-120b, saving $0.13 (100% lower).
High-volume input processingRing-2.6-1T (free)Lower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill.
Long responses and chatbotsRing-2.6-1T (free)Lower output-token price matters most when assistants generate many completion tokens.
RAG or long-document workRing-2.6-1T (free)A larger context window leaves more room for retrieved passages, conversation history, or source files.

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Provider catalogs

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inclusionAI catalog

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OpenAI catalog

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Ring-2.6-1T (free)

Ring-2.6-1T is a 1T-parameter-scale thinking model with 63B active parameters, built for real-world agent workflows that require both strong capability and operational efficiency. It is optimized for coding agents, tool...

gpt-oss-120b

gpt-oss-120b is an open-weight, 117B-parameter Mixture-of-Experts (MoE) language model from OpenAI designed for high-reasoning, agentic, and general-purpose production use cases. It activates 5.1B parameters per forward pass and is optimized...