| Signal | GPT-5.4 Mini | Delta | MiniMax-01 |
|---|---|---|---|
Capabilities | 100 | +67 | |
Benchmarks | 90 | +90 | |
Pricing | 96 | -3 | |
Context window size | 89 | -6 | |
Recency | 100 | +55 | |
Output Capacity | 85 | -15 | |
| Overall Result | 3 wins | of 6 | 3 wins |
Score History
79.3
current score
GPT-5.4 Mini
right now
40
current score
OpenAI
MiniMax
MiniMax-01 saves you $225.00/month
That's $2700.00/year compared to GPT-5.4 Mini at your current usage level of 100K calls/month.
| Metric | GPT-5.4 Mini | MiniMax-01 | Winner |
|---|---|---|---|
| Overall Score | 79 | 40 | GPT-5.4 Mini |
| Rank | #43 | #298 | GPT-5.4 Mini |
| Quality Rank | #43 | #298 | GPT-5.4 Mini |
| Adoption Rank | #43 | #298 | GPT-5.4 Mini |
| Parameters | -- | -- | -- |
| Context Window | 400K | 1000K | MiniMax-01 |
| Pricing | $0.75/$4.50/M | $0.20/$1.10/M | -- |
| Signal Scores | |||
| Capabilities | 100 | 33 | GPT-5.4 Mini |
| Benchmarks | 90 | -- | GPT-5.4 Mini |
| Pricing | 96 | 99 | MiniMax-01 |
| Context window size | 89 | 95 | MiniMax-01 |
| Recency | 100 | 45 | GPT-5.4 Mini |
| Output Capacity | 85 | 100 | MiniMax-01 |
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 79/100 (rank #43), placing it in the top 86% of all 290 models tracked.
Scores 40/100 (rank #298), placing it in the top -2% of all 290 models tracked.
GPT-5.4 Mini has a 39-point advantage, which typically translates to noticeably stronger performance on complex reasoning, code generation, and multi-step tasks.
MiniMax-01 offers 75% better value per quality point. At 1M tokens/day, you'd spend $19.50/month with MiniMax-01 vs $78.75/month with GPT-5.4 Mini - a $59.25 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
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. MiniMax-01 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 ($1.10/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (79/100) 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
GPT-5.4 Mini clearly outperforms MiniMax-01 with a significant 39.3-point lead. For most general use cases, GPT-5.4 Mini is the stronger choice. However, MiniMax-01 may still excel in niche scenarios.
Best for Quality
GPT-5.4 Mini
Marginally better benchmark scores; both are excellent
Best for Cost
MiniMax-01
75% lower pricing; better value at scale
Best for Reliability
GPT-5.4 Mini
Higher uptime and faster response speeds
Best for Prototyping
GPT-5.4 Mini
Stronger community support and better developer experience
Best for Production
GPT-5.4 Mini
Wider enterprise adoption and proven at scale
by OpenAI
| Capability | GPT-5.4 Mini | MiniMax-01 |
|---|---|---|
| Vision (Image Input) | ||
| Function Callingdiffers | ||
| Streaming | ||
| JSON Modediffers | ||
| Reasoningdiffers | ||
| Web Searchdiffers | ||
| Image Output |
OpenAI
MiniMax
MiniMax-01 saves you $5.07/month
That's 75% cheaper than GPT-5.4 Mini 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-5.4 Mini | MiniMax-01 |
|---|---|---|
| Context Window | 400K | 1.0M |
| Max Output Tokens | 128,000 | 1,000,192 |
| Open Source | No | Yes |
| Created | Mar 17, 2026 | Jan 15, 2025 |
MiniMax-01 likely edges ahead due to its significantly lower pricing at $0.20/M input and $1.10/M output compared to GPT-5.4 Mini's $0.75/M and $4.50/M, making it 4.1x cheaper for output tokens. The ranking algorithm appears to weight cost-effectiveness heavily when performance scores are identical, particularly given MiniMax-01's open-source nature which offers additional deployment flexibility.
MiniMax-01's 1M token context window handles repositories 2.5x larger than GPT-5.4 Mini's 400K limit, allowing analysis of approximately 750,000 lines of code versus 300,000 lines. However, GPT-5.4 Mini's function calling and JSON mode capabilities make it superior for automated refactoring tasks, while MiniMax-01 requires manual parsing of structured outputs.
GPT-5.4 Mini's exclusive reasoning capability and web search integration justify the $4.50/M output premium over MiniMax-01's $1.10/M for teams building autonomous coding agents that need real-time documentation lookups. The function calling support alone can reduce integration complexity by 60-80% compared to implementing custom parsing layers for MiniMax-01's raw text outputs.
GPT-5.4 Mini's file->text modality enables direct processing of binary artifacts like compiled configs or log files, while MiniMax-01 requires pre-conversion to text format. For a typical DevOps pipeline processing 10GB of mixed logs daily, GPT-5.4 Mini's native file handling saves approximately 2-3 hours of preprocessing time despite costing $45 versus $11 in output tokens.
The identical 61/100 scores mask critical implementation differences: GPT-5.4 Mini's streaming with function calling enables responsive IDE integrations with <100ms latency, while MiniMax-01's 1M token output capacity allows generating entire microservices (50-100K tokens) in single requests. MiniMax-01's open-source nature also permits on-premise deployment for teams with data residency requirements, offsetting its lack of advanced reasoning features.