# Devstral Small 2 vs ZAYA1-8B

> Devstral Small 2 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/devstral-small-2-vs-zaya1-8b
- Markdown: https://www.anchorterminal.com/compare/devstral-small-2-vs-zaya1-8b.md (~8,850 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 <slug>.grade.anchorterminal.com (the grade as a DNS TXT record, for a sandbox with no HTTP where names still resolve; also top., best.<category>. and <a>.vs.<b>. 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

Devstral Small 2 and ZAYA1-8B score within a point of each other on agent readiness, 61 (C) and 61 (C). Both do open-weight models you run yourself.

- Devstral Small 2: grade C, 61/100, rank #60 of 160 open-weight models. Markdown https://www.anchorterminal.com/tools/devstral-small-2.md · JSON https://www.anchorterminal.com/api/v1/tools/devstral-small-2.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

### Devstral Small 2 (C)

Good for: Developers who want a dependable local coding agent on one consumer GPU or a 32 GB Mac

Ahead on:
- Reach, 90 against 80
- Risk, 60 against 55
- Agent interface, 65 against 60

Watch for: No limitations, safety results, languages or data on the card

### ZAYA1-8B (C)

Good for: People who want a small, fast reasoning model for maths and code and can live without tool calling

Watch for: Tool calling needs a parser that only Zyphra's vLLM fork has


## Why the edge

### Reach: Devstral Small 2 +10

- Devstral Small 2 (90): Memory 25, the smallest build at 4 bits from a runtime's own library is Ollama's devstral-small-2 at Q4_K_M, 15 GB, and 15 GB × 1.2 = 18 GB, within 24 GB. Mistral's own FP8 files are 25.79 GB. Runtimes 25, Released vLLM 0.33.0, SGLang 0.5.23 and Transformers 5.22.2 have the mistral3 model, llama.cpp b12242 has the architecture with a GGUF from its own organisation, and Ollama's library has devstral-small-2. Builds 10, one quantised precision from Mistral, the FP8 weights it releases. Terms 15, Apache 2.0 in the card's metadata and text, an OSI licence with nothing added. Download 10, the Hub API reports gated false on 10 November 2026, so the files download with no account and nothing to accept. Hosted 5, Mistral's own API serves Devstral Small 2: the card says the model is available through its API and points there when a local runtime underperforms. 25 + 25 + 10 + 15 + 10 + 5 = 90.
- 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: Devstral Small 2 +5

- Devstral Small 2 (60): File safety 25, safetensors only, no .bin, .pt or .pth files and no Python in the repository. Provenance 15, files in Mistral's verified mistralai organisation, which Mistral's site links to per our Mistral Large 4 listing (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 5, mistral.ai's security.txt gives a security contact and a submission policy, as read for the Mistral Large 4 listing (5). 25 + 15 + 0 + 0 + 15 + 5 = 60.
- 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.

### Agent interface: Devstral Small 2 +5

- Devstral Small 2 (65): Chat template 20, chat_template.jinja in the repository (11,362 characters), with the tokenizer's tekken file for mistral-common. Tool-calling format 25, the card documents tools in the OpenAI function format with an example, names the mistral tool-call parser with auto tool choice for vLLM, shows the same for SGLang, and ships test prompts with the expected tool-call output. Trained tool calling 10, the card says the model excels at using tools, and its tests cover one tool call and calls made one at a time in sequence. Structured output 0, Nothing on the card about JSON or schema-constrained answers for this model. Reasoning control 0, no reasoning mode is documented, and a June 2026 commit removed stray thinking tokens from the files. Context 10, 256K tokens per the card, served at 262,144 in its vLLM command. 20 + 25 + 10 + 0 + 0 + 10 = 65.
- 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.

## Score by category

| Category | Weight | Devstral Small 2 | ZAYA1-8B | Edge |
| --- | --- | --- | --- | --- |
| Capability | 35%, pending | pending | pending | not scored in this run |
| Reach | 25% (25 this run) | 90 | 80 | Devstral Small 2 +10 |
| Risk | 20% (20 this run) | 60 | 55 | Devstral Small 2 +5 |
| Agent interface | 10% (10 this run) | 65 | 60 | Devstral Small 2 +5 |
| Documentation and upkeep | 10% (10 this run) | 46 | 50 | ZAYA1-8B +4 |
| Negative events | ≤15 | 0 | 0 | |
| **Total** | | **61 · C** | **61 · C** | |

## Facts side by side

| Fact | Devstral Small 2 | ZAYA1-8B |
| --- | --- | --- |
| Kind | Open-weight model | Open-weight model |
| Vendor | Mistral AI | 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 | 2026-07-15 | 2026-07-02 |
| Terms last updated | no document linked | no document linked |
| Privacy policy last updated | no document linked | no document linked |

## Verdicts

**Devstral Small 2.** The easy one to run: a 24B coding agent under Apache 2.0 that five runtimes carry, 15 GB at 4 bits in Ollama, with a 256K context, image input and well-documented tool calling. It's eleven months old, calls tools one at a time, has no reasoning mode, and its card says nothing on limits, safety or 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

### Devstral Small 2

1. `ollama run devstral-small-2` is the quickest start, at 15 GB
2. On vLLM pass `--tool-call-parser mistral --enable-auto-tool-choice`
3. Send the system prompt from CHAT_SYSTEM_PROMPT.txt in the repository. The card says results depend on it
4. Use a low temperature. The repository's default is 0.15
5. Plan for one tool call per turn
6. The same model is on our Mistral API listing if you'd rather not host it

### 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, Devstral Small 2 or ZAYA1-8B?

Devstral Small 2 and ZAYA1-8B score within a point of each other on agent readiness, 61 (C) and 61 (C).


## For agents

- This comparison as JSON: https://www.anchorterminal.com/compare/devstral-small-2-vs-zaya1-8b.json, and with the fewest tokens: https://www.anchorterminal.com/compare/devstral-small-2-vs-zaya1-8b.min.md
- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "devstral-small-2", "b": "zaya1-8b"}`. From a terminal: `anchor compare devstral-small-2 zaya1-8b`
- Each listing in full: https://www.anchorterminal.com/api/v1/tools/devstral-small-2.json and https://www.anchorterminal.com/api/v1/tools/zaya1-8b.json

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- [Devstral Small 2 vs Qwen3.5-397B-A17B](https://www.anchorterminal.com/compare/devstral-small-2-vs-qwen3-5-397b-a17b.md)
- [Devstral Small 2 vs Qwen3.5-4B](https://www.anchorterminal.com/compare/devstral-small-2-vs-qwen3-5-4b.md)
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- [Devstral Small 2 vs Qwen3.6-27B](https://www.anchorterminal.com/compare/devstral-small-2-vs-qwen3-6-27b.md)
- [Devstral Small 2 vs Qwen3.6-35B-A3B](https://www.anchorterminal.com/compare/devstral-small-2-vs-qwen3-6-35b-a3b.md)
- [Devstral Small 2 vs Qwen3.8-27B](https://www.anchorterminal.com/compare/devstral-small-2-vs-qwen3-8-27b.md)
- [Devstral Small 2 vs Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/devstral-small-2-vs-qwen3-8-flash-next.md)
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- [Devstral Small 2 vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/devstral-small-2-vs-swift-1-5-qwen3-8-flash-next.md)
- [Devstral Small 2 vs ThinkingCap (Qwen3.8 27B)](https://www.anchorterminal.com/compare/devstral-small-2-vs-thinkingcap-qwen3-8-27b.md)
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- [LFM3-Omni-2B vs ZAYA1-8B](https://www.anchorterminal.com/compare/lfm3-omni-2b-vs-zaya1-8b.md)
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- [Ling-3.1-flash-1019 vs ZAYA1-8B](https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-zaya1-8b.md)
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- [MiniCPM-V 4.7 1B vs ZAYA1-8B](https://www.anchorterminal.com/compare/minicpm-v-4-7-1b-vs-zaya1-8b.md)
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- [MiniCPM5-2B vs ZAYA1-8B](https://www.anchorterminal.com/compare/minicpm5-2b-vs-zaya1-8b.md)
- [MiniMax-M2.5 vs ZAYA1-8B](https://www.anchorterminal.com/compare/minimax-m2-5-vs-zaya1-8b.md)
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- [MiniMax-M3.1-Flash vs ZAYA1-8B](https://www.anchorterminal.com/compare/minimax-m3-1-flash-vs-zaya1-8b.md)
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- [Qwen3-4B-Instruct-2507 vs ZAYA1-8B](https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-zaya1-8b.md)
- [Qwen3.5-0.8B vs ZAYA1-8B](https://www.anchorterminal.com/compare/qwen3-5-0-8b-vs-zaya1-8b.md)
- [Qwen3.5-122B-A10B vs ZAYA1-8B](https://www.anchorterminal.com/compare/qwen3-5-122b-a10b-vs-zaya1-8b.md)
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- [Qwen3.5-397B-A17B vs ZAYA1-8B](https://www.anchorterminal.com/compare/qwen3-5-397b-a17b-vs-zaya1-8b.md)
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- [Qwen3.5-9B vs ZAYA1-8B](https://www.anchorterminal.com/compare/qwen3-5-9b-vs-zaya1-8b.md)
- [Qwen3.6-27B vs ZAYA1-8B](https://www.anchorterminal.com/compare/qwen3-6-27b-vs-zaya1-8b.md)
- [Qwen3.6-35B-A3B vs ZAYA1-8B](https://www.anchorterminal.com/compare/qwen3-6-35b-a3b-vs-zaya1-8b.md)
- [Qwen3.8-27B vs ZAYA1-8B](https://www.anchorterminal.com/compare/qwen3-8-27b-vs-zaya1-8b.md)
- [Qwen3.8-Flash-Next vs ZAYA1-8B](https://www.anchorterminal.com/compare/qwen3-8-flash-next-vs-zaya1-8b.md)
- [Qwen3-Coder-30B-A3B-Instruct vs ZAYA1-8B](https://www.anchorterminal.com/compare/qwen3-coder-30b-a3b-instruct-vs-zaya1-8b.md)
- [Qwen3-Coder-Next vs ZAYA1-8B](https://www.anchorterminal.com/compare/qwen3-coder-next-vs-zaya1-8b.md)
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- [Qwen3-VL-32B-Instruct vs ZAYA1-8B](https://www.anchorterminal.com/compare/qwen3-vl-32b-instruct-vs-zaya1-8b.md)
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- [Recursive Flint vs ZAYA1-8B](https://www.anchorterminal.com/compare/recursive-flint-vs-zaya1-8b.md)
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- [SenseNova-Loop-9B-Preview vs ZAYA1-8B](https://www.anchorterminal.com/compare/sensenova-loop-9b-preview-vs-zaya1-8b.md)
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- [Spark-X2.6-4B vs ZAYA1-8B](https://www.anchorterminal.com/compare/spark-x2-6-4b-vs-zaya1-8b.md)
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- [Swift 1.5 Qwen3.8-27B vs ZAYA1-8B](https://www.anchorterminal.com/compare/swift-1-5-qwen3-8-27b-vs-zaya1-8b.md)
- [Swift 1.5 Qwen3.8-Flash-Next vs ZAYA1-8B](https://www.anchorterminal.com/compare/swift-1-5-qwen3-8-flash-next-vs-zaya1-8b.md)
- [ThinkingCap (Qwen3.8 27B) vs ZAYA1-8B](https://www.anchorterminal.com/compare/thinkingcap-qwen3-8-27b-vs-zaya1-8b.md)
- [Baidu Unlimited-OCR-2 vs ZAYA1-8B](https://www.anchorterminal.com/compare/unlimited-ocr-2-vs-zaya1-8b.md)
- [WeVisOne-VL-2B vs ZAYA1-8B](https://www.anchorterminal.com/compare/wevisone-vl-2b-vs-zaya1-8b.md)
- [WeVisOne-VL-4B vs ZAYA1-8B](https://www.anchorterminal.com/compare/wevisone-vl-4b-vs-zaya1-8b.md)

---

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