| Signal | Mellum | Delta | autofixer-01 |
|---|---|---|---|
Capabilities | 17 | -- | |
Pricing | 100 | -- | |
Context window size | 0 | -- | |
Recency | 70 | -22 | |
Output Capacity | 20 | -- | |
| Overall Result | 0 wins | of 5 | 1 wins |
Score History
26.4
current score
autofixer-01
right now
31.9
current score
JetBrains
Vercel
| Metric | Mellum | autofixer-01 | Winner |
|---|---|---|---|
| Overall Score | 26 | 32 | autofixer-01 |
| Rank | #336 | #334 | autofixer-01 |
| Quality Rank | #336 | #334 | autofixer-01 |
| Adoption Rank | #336 | #334 | autofixer-01 |
| Parameters | -- | -- | -- |
| Context Window | -- | -- | -- |
| Pricing | Free | Free | -- |
| Signal Scores | |||
| Capabilities | 17 | 17 | Mellum |
| Pricing | 100 | 100 | Mellum |
| Context window size | 0 | 0 | Mellum |
| Recency | 70 | 93 | autofixer-01 |
| Output Capacity | 20 | 20 | Mellum |
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 26/100 (rank #336), placing it in the top -16% of all 290 models tracked.
Scores 32/100 (rank #334), placing it in the top -15% of all 290 models tracked.
autofixer-01 has a 6-point advantage, which typically translates to noticeably better performance on complex reasoning, code generation, and multi-step tasks.
Both models are priced similarly, so the decision comes down to quality and features rather than cost.
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
Based on overall model capabilities and architecture for coding tasks like generating functions, debugging, and refactoring
Customer support chatbot
Suitable for user-facing chat with competitive response times. Mellum also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (0K tokens) can process longer documents, contracts, and research papers in a single pass
Batch data extraction
Lower output pricing ($0.00/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (32/100) correlates with better nuance, coherence, and style in long-form content
autofixer-01 has a moderate advantage with a 5.5-point lead in composite score. It wins on more signal dimensions, but Mellum has specific strengths that could make it the better choice for certain workflows.
Best for Quality
Mellum
Marginally better benchmark scores; both are excellent
Best for Cost
Mellum
0% lower pricing; better value at scale
Best for Reliability
Mellum
Higher uptime and faster response speeds
Best for Prototyping
Mellum
Stronger community support and better developer experience
Best for Production
Mellum
Wider enterprise adoption and proven at scale
by JetBrains
| Capability | Mellum | autofixer-01 |
|---|---|---|
| Vision (Image Input) | ||
| Function Calling | ||
| Streaming | ||
| JSON Mode | ||
| Reasoning | ||
| Web Search | ||
| Image Output |
JetBrains
Vercel
Assumes 60% input / 40% output token ratio per request. Actual costs may vary based on your usage pattern.
| Parameter | Mellum | autofixer-01 |
|---|---|---|
| Context Window | -- | -- |
| Max Output Tokens | -- | -- |
| Open Source | No | No |
| Created | Jun 1, 2025 | Oct 1, 2025 |