| Signal | Ling-2.6-flash (free) | Delta | GLM 5V Turbo |
|---|---|---|---|
Capabilities | 50 | -33 | |
Pricing | 100 | +4 | |
Context window size | 86 | +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 (free) saves you $320.00/month
That's $3840.00/year compared to GLM 5V Turbo at your current usage level of 100K calls/month.
| Metric | Ling-2.6-flash (free) | GLM 5V Turbo | Winner |
|---|---|---|---|
| Overall Score | 40 | 40 | -- |
| Rank | #175 | #177 | Ling-2.6-flash (free) |
| Quality Rank | #175 | #177 | Ling-2.6-flash (free) |
| Adoption Rank | #175 | #177 | Ling-2.6-flash (free) |
| Parameters | -- | -- | -- |
| Context Window | 262K | 203K | Ling-2.6-flash (free) |
| Pricing | Free | $1.20/$4.00/M | -- |
| Signal Scores | |||
| Capabilities | 50 | 83 | GLM 5V Turbo |
| Pricing | 100 | 96 | Ling-2.6-flash (free) |
| Context window size | 86 | 84 | Ling-2.6-flash (free) |
| Recency | 100 | 100 | Ling-2.6-flash (free) |
| 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 #175), placing it in the top 40% of all 290 models tracked.
Scores 40/100 (rank #177), placing it in the top 39% 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.
Compare the cost per quality point to find the best value for your specific workload.
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 (free) 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 ($0.00/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 (free) 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 (free)
Marginally better benchmark scores; both are excellent
Best for Cost
Ling-2.6-flash (free)
100% lower pricing; better value at scale
Best for Reliability
Ling-2.6-flash (free)
Higher uptime and faster response speeds
Best for Prototyping
Ling-2.6-flash (free)
Stronger community support and better developer experience
Best for Production
Ling-2.6-flash (free)
Wider enterprise adoption and proven at scale
by inclusionai
| Capability | Ling-2.6-flash (free) | GLM 5V Turbo |
|---|---|---|
| Vision (Image Input)differs | ||
| Function Calling | ||
| Streaming | ||
| JSON Mode | ||
| Reasoningdiffers | ||
| Web Search | ||
| Image Output |
inclusionai
Zhipu AI
Ling-2.6-flash (free) saves you $6.96/month
That's 100% 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 (free) | 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 |