| Signal | GPT-5.4 Nano | Delta | Ling-2.6-flash |
|---|---|---|---|
Capabilities | 100 | +50 | |
Benchmarks | 90 | +90 | |
Pricing | 99 | -1 | |
Context window size | 89 | +3 | |
Recency | 100 | -- | |
Output Capacity | 85 | +10 | |
| Overall Result | 4 wins | of 6 | 1 wins |
Score History
79.3
current score
GPT-5.4 Nano
right now
40
current score
OpenAI
inclusionai
Ling-2.6-flash saves you $62.50/month
That's $750.00/year compared to GPT-5.4 Nano at your current usage level of 100K calls/month.
| Metric | GPT-5.4 Nano | Ling-2.6-flash | Winner |
|---|---|---|---|
| Overall Score | 79 | 40 | GPT-5.4 Nano |
| Rank | #42 | #203 | GPT-5.4 Nano |
| Quality Rank | #42 | #203 | GPT-5.4 Nano |
| Adoption Rank | #42 | #203 | GPT-5.4 Nano |
| Parameters | -- | -- | -- |
| Context Window | 400K | 262K | GPT-5.4 Nano |
| Pricing | $0.20/$1.25/M | $0.08/$0.24/M | -- |
| Signal Scores | |||
| Capabilities | 100 | 50 | GPT-5.4 Nano |
| Benchmarks | 90 | -- | GPT-5.4 Nano |
| Pricing | 99 | 100 | Ling-2.6-flash |
| Context window size | 89 | 86 | GPT-5.4 Nano |
| Recency | 100 | 100 | GPT-5.4 Nano |
| Output Capacity | 85 | 75 | GPT-5.4 Nano |
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 #42), placing it in the top 86% of all 290 models tracked.
Scores 40/100 (rank #203), placing it in the top 30% of all 290 models tracked.
GPT-5.4 Nano has a 39-point advantage, which typically translates to noticeably stronger performance on complex reasoning, code generation, and multi-step tasks.
Ling-2.6-flash offers 78% better value per quality point. At 1M tokens/day, you'd spend $4.80/month with Ling-2.6-flash vs $21.75/month with GPT-5.4 Nano - a $16.95 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. Ling-2.6-flash also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (400K tokens) can process longer documents, contracts, and research papers in a single pass
Batch data extraction
Lower output pricing ($0.24/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 Nano clearly outperforms Ling-2.6-flash with a significant 39.3-point lead. For most general use cases, GPT-5.4 Nano is the stronger choice. However, Ling-2.6-flash may still excel in niche scenarios.
Best for Quality
GPT-5.4 Nano
Marginally better benchmark scores; both are excellent
Best for Cost
Ling-2.6-flash
78% lower pricing; better value at scale
Best for Reliability
GPT-5.4 Nano
Higher uptime and faster response speeds
Best for Prototyping
GPT-5.4 Nano
Stronger community support and better developer experience
Best for Production
GPT-5.4 Nano
Wider enterprise adoption and proven at scale
by OpenAI
| Capability | GPT-5.4 Nano | Ling-2.6-flash |
|---|---|---|
| Vision (Image Input)differs | ||
| Function Calling | ||
| Streaming | ||
| JSON Mode | ||
| Reasoningdiffers | ||
| Web Searchdiffers | ||
| Image Output |
OpenAI
inclusionai
Ling-2.6-flash saves you $1.43/month
That's 77% cheaper than GPT-5.4 Nano 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 Nano | Ling-2.6-flash |
|---|---|---|
| Context Window | 400K | 262K |
| Max Output Tokens | 128,000 | 32,768 |
| Open Source | No | No |
| Created | Mar 17, 2026 | Apr 21, 2026 |