| Signal | Ling-2.6-flash | Delta | GLM 5V Turbo |
|---|---|---|---|
Capabilities | 50 | -33 | |
Pricing | 100 | +4 | |
Context window size | 77 | +2 | |
Recency | 100 | -- | |
Output Capacity | 75 | -10 | |
| Overall Result | 2 wins | of 5 | 2 wins |
Score History
40
current score
Tied
right now
40
current score
inclusionai
Zhipu AI
Ling-2.6-flash saves you $317.50/month
That's $3810.00/year compared to GLM 5V Turbo at your current usage level of 100K calls/month.
| Metric | Ling-2.6-flash | GLM 5V Turbo | Winner |
|---|---|---|---|
| Overall Score | 40 | 40 | -- |
| Rank | #196 | #198 | Ling-2.6-flash |
| Quality Rank | #196 | #198 | Ling-2.6-flash |
| Adoption Rank | #196 | #198 | Ling-2.6-flash |
| Parameters | -- | -- | -- |
| Context Window | 262K | 203K | Ling-2.6-flash |
| Pricing | $0.01/$0.03/M | $1.20/$4.00/M | -- |
| Signal Scores | |||
| Capabilities | 50 | 83 | GLM 5V Turbo |
| Pricing | 100 | 96 | Ling-2.6-flash |
| Context window size | 77 | 76 | Ling-2.6-flash |
| Recency | 100 | 100 | Ling-2.6-flash |
| Output Capacity | 75 | 85 | GLM 5V Turbo |
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 40/100 (rank #196), placing it in the top 33% of all 290 models tracked.
Scores 40/100 (rank #198), placing it in the top 32% 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.
Ling-2.6-flash offers 99% better value per quality point. At 1M tokens/day, you'd spend $0.60/month with Ling-2.6-flash vs $78.00/month with GLM 5V Turbo - a $77.40 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
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 (262K tokens) can process longer documents, contracts, and research papers in a single pass
Batch data extraction
Lower output pricing ($0.03/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (40/100) 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
Ling-2.6-flash and GLM 5V Turbo are extremely close in overall performance (only 0 points apart). Your best choice depends entirely on which specific strengths matter most for your use case.
Best for Quality
Ling-2.6-flash
Marginally better benchmark scores; both are excellent
Best for Cost
Ling-2.6-flash
99% lower pricing; better value at scale
Best for Reliability
Ling-2.6-flash
Higher uptime and faster response speeds
Best for Prototyping
Ling-2.6-flash
Stronger community support and better developer experience
Best for Production
Ling-2.6-flash
Wider enterprise adoption and proven at scale
by inclusionai
| Capability | Ling-2.6-flash | GLM 5V Turbo |
|---|---|---|
| Vision (Image Input)differs | ||
| Function Calling | ||
| Streaming | ||
| JSON Mode | ||
| Reasoningdiffers | ||
| Web Search | ||
| Image Output |
inclusionai
Zhipu AI
Ling-2.6-flash saves you $6.91/month
That's 99% cheaper than GLM 5V Turbo 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 | Ling-2.6-flash | GLM 5V Turbo |
|---|---|---|
| Context Window | 262K | 203K |
| Max Output Tokens | 32,768 | 131,072 |
| Open Source | No | No |
| Created | Apr 21, 2026 | Apr 1, 2026 |