| Signal | gpt-oss-20b | Delta | MiniMax M2-her |
|---|---|---|---|
Capabilities | 67 | +50 | |
Benchmarks | 56 | -5 | |
Pricing | 100 | +1 | |
Context window size | 81 | +5 | |
Recency | 88 | -12 | |
Output Capacity | 85 | +30 | |
| Overall Result | 4 wins | of 6 | 2 wins |
Score History
57.6
current score
gpt-oss-20b
right now
57.3
current score
OpenAI
MiniMax
gpt-oss-20b saves you $81.50/month
That's $978.00/year compared to MiniMax M2-her at your current usage level of 100K calls/month.
| Metric | gpt-oss-20b | MiniMax M2-her | Winner |
|---|---|---|---|
| Overall Score | 58 | 57 | gpt-oss-20b |
| Rank | #139 | #140 | gpt-oss-20b |
| Quality Rank | #139 | #140 | gpt-oss-20b |
| Adoption Rank | #139 | #140 | gpt-oss-20b |
| Parameters | 20B | -- | -- |
| Context Window | 131K | 66K | gpt-oss-20b |
| Pricing | $0.03/$0.11/M | $0.30/$1.20/M | -- |
| Signal Scores | |||
| Capabilities | 67 | 17 | gpt-oss-20b |
| Benchmarks | 56 | 61 | MiniMax M2-her |
| Pricing | 100 | 99 | gpt-oss-20b |
| Context window size | 81 | 76 | gpt-oss-20b |
| Recency | 88 | 100 | MiniMax M2-her |
| Output Capacity | 85 | 55 | gpt-oss-20b |
Our score (0-100) is driven by benchmark performance (90%) from Arena Elo ratings, MMLU, GPQA, HumanEval, SWE-bench, and 15+ standardized evaluations. Capabilities and context window serve as tiebreakers (10%). Learn more about our methodology.
Scores 58/100 (rank #139), placing it in the top 52% of all 290 models tracked.
Scores 57/100 (rank #140), placing it in the top 52% of all 290 models tracked.
With only a 0-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-20b offers 91% better value per quality point. At 1M tokens/day, you'd spend $2.10/month with gpt-oss-20b vs $22.50/month with MiniMax M2-her - a $20.40 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-20b also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (131K tokens) can process longer documents, contracts, and research papers in a single pass
Batch data extraction
Lower output pricing ($0.11/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (58/100) correlates with better nuance, coherence, and style in long-form content
gpt-oss-20b and MiniMax M2-her are extremely close in overall performance (only 0.30000000000000426 points apart). Your best choice depends entirely on which specific strengths matter most for your use case.
Best for Quality
gpt-oss-20b
Marginally better benchmark scores; both are excellent
Best for Cost
gpt-oss-20b
91% lower pricing; better value at scale
Best for Reliability
gpt-oss-20b
Higher uptime and faster response speeds
Best for Prototyping
gpt-oss-20b
Stronger community support and better developer experience
Best for Production
gpt-oss-20b
Wider enterprise adoption and proven at scale
by OpenAI
| Capability | gpt-oss-20b | MiniMax M2-her |
|---|---|---|
| Vision (Image Input) | ||
| Function Callingdiffers | ||
| Streaming | ||
| JSON Modediffers | ||
| Reasoningdiffers | ||
| Web Search | ||
| Image Output |
OpenAI
MiniMax
gpt-oss-20b saves you $1.79/month
That's 91% cheaper than MiniMax M2-her 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-20b | MiniMax M2-her |
|---|---|---|
| Context Window | 131K | 66K |
| Max Output Tokens | 131,072 | 2,048 |
| Open Source | Yes | No |
| Created | Aug 5, 2025 | Jan 23, 2026 |
gpt-oss-20b scores 58/100 (rank #139) compared to MiniMax M2-her's 57/100 (rank #140), giving it a 0-point advantage. gpt-oss-20b is the stronger overall choice, though MiniMax M2-her may excel in specific areas like certain benchmarks.
gpt-oss-20b is ranked #139 and MiniMax M2-her is ranked #140 out of 290+ AI models. Rankings use a composite score combining benchmark performance (90%) from MMLU, GPQA, HumanEval, SWE-bench, and 15+ standardized evaluations, with capabilities and context window as tiebreakers (10%). Scores update hourly.
gpt-oss-20b is cheaper at $0.11/M output tokens vs MiniMax M2-her's $1.20/M output tokens - 10.9x more expensive. Input token pricing: gpt-oss-20b at $0.03/M vs MiniMax M2-her at $0.30/M.
gpt-oss-20b has a larger context window of 131,072 tokens compared to MiniMax M2-her's 65,536 tokens. A larger context window means the model can process longer documents and conversations.