| Signal | gpt-oss-safeguard-20b | Delta | Qwen3.5 Plus 2026-02-15 |
|---|---|---|---|
Capabilities | 67 | -17 | |
Pricing | 0 | -1 | |
Context window size | 81 | -14 | |
Recency | 100 | -- | |
Output Capacity | 80 | -- | |
| Overall Result | 0 wins | of 5 | 3 wins |
3
days ranked higher
1
days
26
days ranked higher
OpenAI
Alibaba
gpt-oss-safeguard-20b saves you $81.50/month
That's $978.00/year compared to Qwen3.5 Plus 2026-02-15 at your current usage level of 100K calls/month.
| Metric | gpt-oss-safeguard-20b | Qwen3.5 Plus 2026-02-15 | Winner |
|---|---|---|---|
| Overall Score | 82 | 85 | Qwen3.5 Plus 2026-02-15 |
| Rank | #68 | #30 | Qwen3.5 Plus 2026-02-15 |
| Quality Rank | #68 | #30 | Qwen3.5 Plus 2026-02-15 |
| Adoption Rank | #68 | #30 | Qwen3.5 Plus 2026-02-15 |
| Parameters | 20B | -- | -- |
| Context Window | 131K | 1000K | Qwen3.5 Plus 2026-02-15 |
| Pricing | $0.07/$0.30/M | $0.26/$1.56/M | -- |
| Signal Scores | |||
| Capabilities | 67 | 83 | Qwen3.5 Plus 2026-02-15 |
| Pricing | 0 | 2 | Qwen3.5 Plus 2026-02-15 |
| Context window size | 81 | 95 | Qwen3.5 Plus 2026-02-15 |
| Recency | 100 | 100 | gpt-oss-safeguard-20b |
| Output Capacity | 80 | 80 | gpt-oss-safeguard-20b |
Our composite score (0–100) combines six weighted signals: benchmark performance (25%), pricing efficiency (25%), context window size (15%), model recency (15%), output capacity (10%), and capability versatility (10%). Here's what the scores mean for these two models:
Scores 82/100 (rank #68), placing it in the top 77% of all 290 models tracked.
Scores 85/100 (rank #30), placing it in the top 90% of all 290 models tracked.
With only a 3-point gap, these models are in the same performance tier. The practical difference in output quality is minimal - your choice should depend on pricing, latency requirements, and specific feature needs.
gpt-oss-safeguard-20b offers 79% better value per quality point. At 1M tokens/day, you'd spend $5.63/month with gpt-oss-safeguard-20b vs $27.30/month with Qwen3.5 Plus 2026-02-15 - a $21.68 monthly difference.
Both models have comparable response speeds. For most applications, the latency difference is negligible.
When latency matters most: Interactive chatbots, IDE code completion, real-time translation, and user-facing applications where response time directly impacts experience. For batch processing, background summarization, or offline analysis, latency is less critical.
Code generation & review
Higher benchmark score (0/100) indicates stronger performance on coding tasks like generating functions, debugging, and refactoring
Customer support chatbot
Faster response time (speed score 0/100) is critical for user-facing chat. gpt-oss-safeguard-20b also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (1000K tokens) can process longer documents, contracts, and research papers in a single pass
Batch data extraction
Lower output pricing ($0.30/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (85/100) correlates with better nuance, coherence, and style in long-form content
Image understanding & OCR
Supports vision input - can analyze screenshots, diagrams, photos, and scanned documents directly
Qwen3.5 Plus 2026-02-15 has a moderate advantage with a 3.4000000000000057-point lead in composite score. It wins on more signal dimensions, but gpt-oss-safeguard-20b has specific strengths that could make it the better choice for certain workflows.
Best for Quality
gpt-oss-safeguard-20b
Marginally better benchmark scores; both are excellent
Best for Cost
gpt-oss-safeguard-20b
79% lower pricing; better value at scale
Best for Reliability
gpt-oss-safeguard-20b
Higher uptime and faster response speeds
Best for Prototyping
gpt-oss-safeguard-20b
Stronger community support and better developer experience
Best for Production
gpt-oss-safeguard-20b
Wider enterprise adoption and proven at scale
by OpenAI
| Capability | gpt-oss-safeguard-20b | Qwen3.5 Plus 2026-02-15 |
|---|---|---|
| Vision (Image Input)differs | ||
| Function Calling | ||
| Streaming | ||
| JSON Mode | ||
| Reasoning | ||
| Web Search | ||
| Image Output |
OpenAI
Alibaba
gpt-oss-safeguard-20b saves you $1.85/month
That's 79% cheaper than Qwen3.5 Plus 2026-02-15 at 1,000 tokens/request and 100 requests/day.
Assumes 60% input / 40% output token ratio per request. Actual costs may vary based on your usage pattern.
| Parameter | gpt-oss-safeguard-20b | Qwen3.5 Plus 2026-02-15 |
|---|---|---|
| Context Window | 131K | 1M |
| Max Output Tokens | 65,536 | 65,536 |
| Open Source | Yes | No |
| Created | Oct 29, 2025 | Feb 16, 2026 |
Qwen3.5 Plus 2026-02-15 scores 85/100 (rank #30) compared to gpt-oss-safeguard-20b's 82/100 (rank #68), giving it a 3-point advantage. Qwen3.5 Plus 2026-02-15 is the stronger overall choice, though gpt-oss-safeguard-20b may excel in specific areas like cost efficiency.
gpt-oss-safeguard-20b is ranked #68 and Qwen3.5 Plus 2026-02-15 is ranked #30 out of 290+ AI models. Rankings use a composite score combining benchmark performance (25%), pricing (25%), context window (15%), recency (15%), output capacity (10%), and versatility (10%). Scores update hourly.
gpt-oss-safeguard-20b is cheaper at $0.30/M output tokens vs Qwen3.5 Plus 2026-02-15's $1.56/M output tokens - 5.2x more expensive. Input token pricing: gpt-oss-safeguard-20b at $0.07/M vs Qwen3.5 Plus 2026-02-15 at $0.26/M.
Qwen3.5 Plus 2026-02-15 has a larger context window of 1,000,000 tokens compared to gpt-oss-safeguard-20b's 131,072 tokens. A larger context window means the model can process longer documents and conversations.