gpt-oss-safeguard-20bvs Kimi K2 Thinking
Kimi K2 Thinking
Compare performance metrics, pricing, and capabilities of these AI models.
Key Differences
Context Length
Lower
gpt-oss-safeguard-20b: 131K (disadvantage)
Kimi K2 Thinking: 262K (advantage)
Cost Efficiency
Lower Cost
Prompt: $0.07M vs $0.55M
Completion: $0.30M vs $2.25M
Capabilities
gpt-oss-safeguard-20b
Modality: text->text
Inputs: text
Kimi K2 Thinking
Modality: text->text
Inputs: text
O
gpt-oss-safeguard-20b
openai/gpt-oss-safeguard-20b
gpt-oss-safeguard-20b is a safety reasoning model from OpenAI built upon gpt-oss-20b. This open-weight, 21B-parameter Mixture-of-Experts (MoE) model o...
Context Length131K
Prompt Price$0.07M
ReleasedOctober 29, 2025
Supports:
text->textM
Kimi K2 Thinking
moonshotai/kimi-k2-thinking
Kimi K2 Thinking is Moonshot AI’s most advanced open reasoning model to date, extending the K2 series into agentic, long-horizon reasoning. Built on t...
Context Length262K
Prompt Price$0.55M
ReleasedNovember 6, 2025
Supports:
text->textDetailed Comparison
| Feature | | Kimi K2 Thinking |
|---|---|---|
| Context Length | 131K | 262K |
| Prompt Price | $0.07M | $0.55M |
| Completion Price | $0.30M | $2.25M |
| Modality | text->text | text->text |
| Release Date | October 29, 2025 | November 6, 2025 |
Analysis & Recommendations
Quick Summary
This comparison reveals key trade-offs between gpt-oss-safeguard-20b and Kimi K2 Thinking. Kimi K2 Thinking offers a larger context window of 262K compared to gpt-oss-safeguard-20b's 131K, though Kimi K2 Thinking comes at a higher cost.
gpt-oss-safeguard-20b Strengths
- •Competitive context size (131K)
- •More cost-effective per token
- •Specialized for text tasks
- •Proven and stable model
Kimi K2 Thinking Strengths
- •Larger context window (262K) for processing longer documents
- •Premium pricing for high-quality output
- •Specialized for text tasks
- •Latest generation model
When to Use Each Model
Choose gpt-oss-safeguard-20b when:
- • You need competitive context capability for complex tasks
- • Cost efficiency is important in your use case
- • Working with text-based tasks that benefit from deep analysis
Choose Kimi K2 Thinking when:
- • You need the larger context window for long-form content
- • Cost efficiency is not the primary concern for your budget
- • Working with text-based tasks that require advanced processing
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