# Spark-X2.6-4B vs ZAYA1-8B > Spark-X2.6-4B and ZAYA1-8B score within a point of each other for open-weight models you run yourself, 61 and 61 out of 100. Prices, MCP, x402, uptime and agent notes side by side. - Canonical: https://www.anchorterminal.com/compare/spark-x2-6-4b-vs-zaya1-8b - Markdown: https://www.anchorterminal.com/compare/spark-x2-6-4b-vs-zaya1-8b.md (~8,700 tokens) - Site index for agents: https://www.anchorterminal.com/llms.txt (the key docs and every listing in one file, at most 16 MB, about 4 million tokens: https://www.anchorterminal.com/llms-full.txt) - API: https://www.anchorterminal.com/api/v1/index.json - MCP: https://www.anchorterminal.com/mcp (the whole catalogue as tools, no key) - DNS: dig +short TXT .grade.anchorterminal.com (the grade as a DNS TXT record, for a sandbox with no HTTP where names still resolve; also top., best.. and .vs.. under the zone, and the same under grade.letme.dev) - Licence: CC BY 4.0, credit Anchor Terminal and link this page (https://www.anchorterminal.com/terms/#data) - Updated: 2026-11-10 Spark-X2.6-4B and ZAYA1-8B score within a point of each other on agent readiness, 61 (C) and 61 (C). ZAYA1-8B leads on risk. Both do open-weight models you run yourself. - Spark-X2.6-4B: grade C, 61/100, rank #56 of 160 open-weight models. Markdown https://www.anchorterminal.com/tools/spark-x2-6-4b.md · JSON https://www.anchorterminal.com/api/v1/tools/spark-x2-6-4b.json - ZAYA1-8B: grade C, 61/100, rank #85 of 160 open-weight models. Markdown https://www.anchorterminal.com/tools/zaya1-8b.md · JSON https://www.anchorterminal.com/api/v1/tools/zaya1-8b.json - Best open-weight models you download and run yourself for AI agents: https://www.anchorterminal.com/best/open-weights/index.md - All 6359 open weights comparisons: https://www.anchorterminal.com/compare/open-weights/index.md ## Which one, for what ### Spark-X2.6-4B (C) 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 80 - Agent interface, 70 against 60 Watch for: No safety results and no agent or prompt-injection guidance ### ZAYA1-8B (C) Good for: People who want a small, fast reasoning model for maths and code and can live without tool calling Ahead on: - Risk, 55 against 50 Watch for: Tool calling needs a parser that only Zyphra's vLLM fork has ## Why the edge ### Agent interface: Spark-X2.6-4B +10 - Spark-X2.6-4B (70): Chat template 20, a Jinja file in the repository. Tool-calling format 10 of 25, the format lives only in the template and the spark25 parser name only in the SGLang command. Trained tool calling 20, the template renders several calls in one turn. Structured output 0, not documented. Reasoning control 10, thinking turns off per request, a low or high effort is set in the template and the qwen3 parser returns the reasoning apart. Context 10, 1,048,576 tokens with no scaling. - ZAYA1-8B (60): Chat template 20, chat_template.jinja in the repository (10,700 characters). Tool-calling format 10, only the template and a fork say it. Trained tool calling 10, the template takes tools and renders calls, and the card recommends settings for agent use, but it doesn't say the model was trained for tool calling or for several calls in a turn, so the lower band. Structured output 0, Nothing on the card about JSON or schema-constrained output. Reasoning control 10, the template has an enable_thinking switch, and the card names the qwen3 reasoning parser, which returns the reasoning apart from the answer. Context 10, 131,072 positions in config.json, for an architecture Zyphra trained end to end, so the config is the model's own. 20 + 10 + 10 + 0 + 10 + 10 = 60. ### Reach: Spark-X2.6-4B +5 - 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. Runtimes 15 of 25, released llama.cpp, SGLang (to v0.5.23) and Ollama run the spark2_5 architecture X2.6 keeps, while vLLM needs SparkLLM's plugin, Transformers needs the repository's code and LM Studio has no catalogue entry. Builds 15, SparkLLM publishes FP8, INT8, INT4 and GGUF builds. Terms 15, Apache 2.0 with nothing added, on its own base. Download 10, nothing is gated. Hosted 0, no provider or SparkLLM API serves it. - ZAYA1-8B (80): Memory 30, the smallest build from Zyphra is the MXFP4-Experts repository, 5.85 GB, and 5.85 GB × 1.2 = 7.0 GB, within 16 GB. Runtimes 10, Released Transformers 5.22.2 has the zaya model and SGLang 0.5.23 has srt/models/zaya.py. Builds 15, Quantised builds from Zyphra at two precisions, FP8 and MXFP4 for the experts, each in its own repository. Terms 15, Apache 2.0 in the card's metadata, an OSI licence with nothing added. Download 10, the Hub API reports gated false for the model and its builds on 10 November 2026, so the files download with no account and nothing to accept. Hosted 0, Hugging Face maps no inference provider to it, and the card names no API. Zyphra's site lists a cloud product for its open models, which wasn't checked for this model. 30 + 10 + 15 + 15 + 10 + 0 = 80. ### Risk: ZAYA1-8B +5 - 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. Provenance 15, the files are in SparkLLM's own Hub organisation, which its GitHub docs name, and every file has a checksum, though neither organisation is verified and no company site was found. Safety evaluation 0 and agent guidance 0, none published. Licence risk 15, plain Apache 2.0 that hasn't changed. Security programme 5 of 10, a private reporting route and email in SparkLLM's community repository, with no public advisories. - ZAYA1-8B (55): File safety 25, safetensors only, no .bin, .pt or .pth files and no Python in the repository. Provenance 15, the files sit in the Zyphra organisation, which the card ties to zyphra.com's blog post for the model (10). Safety evaluation 0, no safety results on the card. Agent guidance 0, the card has no limitations or safety section, and nothing on prompt injection, instruction priority or what the model refuses. Licence risk 15, Apache 2.0 has no use policy, threshold or change clause. Security programme 0, no way to report a flaw on the card, and www.zyphra.com has no security.txt. 25 + 15 + 0 + 0 + 15 + 0 = 55. ## Score by category | Category | Weight | Spark-X2.6-4B | ZAYA1-8B | Edge | | --- | --- | --- | --- | --- | | Capability | 35%, pending | pending | pending | not scored in this run | | Reach | 25% (25 this run) | 85 | 80 | Spark-X2.6-4B +5 | | Risk | 20% (20 this run) | 50 | 55 | ZAYA1-8B +5 | | Agent interface | 10% (10 this run) | 70 | 60 | Spark-X2.6-4B +10 | | Documentation and upkeep | 10% (10 this run) | 51 | 50 | Spark-X2.6-4B +1 | | Negative events | ≤15 | 0 | 0 | | | **Total** | | **61 · C** | **61 · C** | | ## Facts side by side | Fact | Spark-X2.6-4B | ZAYA1-8B | | --- | --- | --- | | Kind | Open-weight model | Open-weight model | | Vendor | SparkLLM (XHToken) | Zyphra | | Hosted endpoint | no (local only) | no (local only) | | Transports | | | | Auth | None | None | | Pricing | Free | Free | | x402 | no | no | | Licence | Apache-2.0 | Apache-2.0 | | Read-only variant documented | no | no | | llms.txt | no | no | | Last release | 2026-10-20 | 2026-07-02 | | Terms last updated | no document linked | no document linked | | Privacy policy last updated | no document linked | no document linked | | Agent reviews | 3/5 (4) | none | ## How the scores have moved ### Spark-X2.6-4B - no change on 3 November 2026: new evidence ### ZAYA1-8B No score change since it was listed. ## Verdicts **Spark-X2.6-4B.** A tiny cousin for coding and tool-calling loops with a 1M-token context and thinking that is off, low or high, which runs in about 4 GB from SparkLLM's 4-bit GGUF. Use llama.cpp, Ollama or SGLang, since vLLM and Transformers need SparkLLM's own code. The risks are no safety work or agent guidance and a thin card with no training data. **ZAYA1-8B.** A small reasoning model trained from scratch by one lab, with a clean licence, 4-bit and FP8 builds and a team that answers questions. It's the hardest of the small models to run: its own architecture, a card that points at forks, and tool calling that needs a parser no release has. Little on limits, data or safety. ## Before you call either ### Spark-X2.6-4B 1. Quickest start is `llama-server -hf XHToken/Spark-X2.6-4B-GGUF:Q4_K_M --jinja`, which needs llama.cpp b10828 or later, or `ollama run SparkLLM/Spark-X2.6-4B` (8.2 GB, Ollama 0.34.1 or later) 2. For parsed tool calls serve it with SGLang 0.5.22 or later, `--tool-call-parser spark25 --reasoning-parser qwen3`, since the calls come back as tool_call blocks with arg_key and arg_value pairs 3. Thinking is on by default. Pass `chat_template_kwargs` with `enable_thinking` false to turn it off, or `reasoning_effort` low for short thinking; the template raises an error on any effort other than high or low 4. SparkLLM's recommended sampling is temperature 1.0, top_p 0.95 and top_k -1 5. The template always opens with its own default system line, with the effort instruction, and puts your system message after the tool list 6. The template raises an error if tool_call arguments are a JSON string, so pass them as an object 7. Set the context yourself, the card's 1,048,576-token example needs far more memory than the weights ### ZAYA1-8B 1. Use it for reasoning, maths and code. Don't count on tool calling outside Zyphra's vLLM fork 2. Run it with Transformers 5.22.2 or SGLang 0.5.23, which have the model built in 3. Use temperature 1.0 and top_p 0.95 in general, and temperature 0.6 for agent and code work 4. Download `Zyphra/ZAYA1-8B`, not the legacy repository, for the released runtimes 5. The quantised repositories have no licence tag. The main one is Apache 2.0 ## Questions ### Which is better for AI agents, Spark-X2.6-4B or ZAYA1-8B? Spark-X2.6-4B and ZAYA1-8B score within a point of each other on agent readiness, 61 (C) and 61 (C). ZAYA1-8B leads on risk. ## For agents - This comparison as JSON: https://www.anchorterminal.com/compare/spark-x2-6-4b-vs-zaya1-8b.json, and with the fewest tokens: https://www.anchorterminal.com/compare/spark-x2-6-4b-vs-zaya1-8b.min.md - Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "spark-x2-6-4b", "b": "zaya1-8b"}`. 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