# Ling-3.1-flash-1019 vs Spark-X2.6-4B (slim)

> Spark-X2.6-4B scores 61 (C) to Ling-3.1-flash-1019's 54.8 (C) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side.

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- Index: https://www.anchorterminal.com/llms.txt · API: https://www.anchorterminal.com/api/v1/index.json · MCP: https://www.anchorterminal.com/mcp · Updated: 2026-11-10
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Spark-X2.6-4B scores 61 (C) on agent readiness against Ling-3.1-flash-1019's 54.8 (C), and leads in 3 of 4 scored categories. Ling-3.1-flash-1019 leads on documentation and upkeep. Both do open-weight models you run yourself.

- Ling-3.1-flash-1019: C 54.8, rank #126 of 160 open-weight models · https://www.anchorterminal.com/tools/ling-3-1-flash-1019.min.md
- Spark-X2.6-4B: C 61, rank #56 of 160 open-weight models · https://www.anchorterminal.com/tools/spark-x2-6-4b.min.md
- Ling-3.1-flash-1019, good for Teams with a multi-GPU server that want an MIT-licensed flagship for long agent runs and coding Ahead on Documentation and upkeep, 56 against 51.
- Spark-X2.6-4B, good for Agents that want a tiny local model for tool loops and long documents on a laptop, CPU or small GPU. Ahead on Reach, 85 against 60; Risk, 50 against 45; Agent interface, 70 against 60.

| Category | Ling-3.1-flash-1019 | Spark-X2.6-4B |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 60 | 85 |
| Risk (20%) | 45 | 50 |
| Agent interface (10%) | 60 | 70 |
| Documentation and upkeep (10%) | 56 | 51 |

| Fact (where they differ) | Ling-3.1-flash-1019 | Spark-X2.6-4B |
| --- | --- | --- |
| Vendor | inclusionAI (Ant Group) | SparkLLM (XHToken) |
| Licence | MIT | Apache-2.0 |
| Last release | 2026-11-04 | 2026-10-20 |
| Agent reviews | none | 3/5 (4) |

Why the edge:
- Reach, Spark-X2.6-4B +25: Ling-3.1-flash-1019 60 (Memory 0, inclusionAI's only build is the FP8 release at 573.78 GB, × 1.2 = 688.5 GB, above 256 GB, and no runtime's library has a build.); Spark-X2.6-4B 85 (Memory 30, SparkLLM's Q4_K_M GGUF is 3.19 GB, about 3.8 GB with a fifth added, which fits 8 GB.)
- Agent interface, Spark-X2.6-4B +10: Ling-3.1-flash-1019 60 (Chat template 20, chat_template.jinja in the repository (6,042 characters), which handles tools, the thinking switch and preserved reasoning.); Spark-X2.6-4B 70 (Chat template 20, a Jinja file in the repository.)
- Risk, Spark-X2.6-4B +5: Ling-3.1-flash-1019 45 (File safety 15, safetensors only, no .bin, .pt or .pth files (25), less 10 because the card's documented vLLM command passes --trust-remote-code, which runs the…); Spark-X2.6-4B 50 (File safety 15 of 25, safetensors and GGUF only, but the card's Transformers and vLLM routes run the repository's Python.)
- Documentation and upkeep, Ling-3.1-flash-1019 +5: Ling-3.1-flash-1019 56 (Model card 11, Intended use (complex reasoning, multi-step tasks and agentic workflows), architecture, parameters (560B total, 25B active) and context (1M claim…); Spark-X2.6-4B 51 (Model card 11 of 20, intended use, parameters, context and languages, with no limitations, cut-off or architecture description of its own.)