Recommendation for Charts & diagrams

Charts & Diagrams

Our top recommendation for Charts & Diagrams, based on the public evidence we track, is Anthropic: Claude Opus 4.6. Anthropic: Claude Fable 5 is the next-ranked alternative.

About this recommendation

Updated
Sep 25, 2026
Evidence through
Sep 25, 2026
Sources
3
Revision
v77

Decision audit

Why this result

Inspect the inputs and the computed order behind the recommendation.

Models screened

20

live candidates

Evaluation feeds

5

task-weighted

Winner coverage

38%

intended feed weight

Largest provider share

2 of 3

Anthropic

Provisional source breadth. 4 citation families and 0 practitioner families support the top result; 0 cautionary threads is retained. The largest citation family contributes 40%.

Sources evaluated

The task sets these weights before any model is scored.

winner: Claude Opus 4.6
Evaluation feedWeightWinner resultField measured
VLMEvalKit tasksunavailable
40%
feed unavailable0/20
LMArena Document
20%
#314/20
LMArena Vision
15%
#317/20
Structured-output evalunavailable
15%
feed unavailable0/20
OpenRouter usage
10%
83/10020/20

Provider concentration

Each exact model is scored separately; provider identity is not a ranking input.

Anthropic67%
  • Anthropic2 models
  • deepseek1 model

Decision table

Every published model is shown in computed order. Practitioner sources are distinct community threads, not the citations repeated in the prose below.

RankModelRelative scoreCoveragePractitioner evidenceStrongest measured reason
01Claude Opus 4.6Anthropic
54
38%no linked practitioner threads#3 LMArena Document · #3 LMArena Vision
02Claude Fable 5Anthropic
53
38%no linked practitioner threads#1 LMArena Vision · #4 LMArena Document
03DeepSeek V4 Flash Vision Expdeepseek
47
11%5 threads · 4 families · 1 cautionsOpenRouter usage 86/100 normalized

Relative score combines normalized benchmark quality and signal coverage; independent practitioner evidence and freshness are bounded tie-breakers. It is an ordering score, not an absolute quality percentage. The writing model receives this order and cannot change it.

  1. 01

    Anthropic: Claude Opus 4.6

    Anthropic: Claude Opus 4.6 ranks #3 of 71 on LMArena's vision arena (Elo 1299), based on human preference on image-understanding tasks.

    Best when: Consider only after reviewing the cited caution.

  2. 02

    Anthropic: Claude Fable 5

    Anthropic: Claude Fable 5 ranks #1 of 71 on LMArena's vision arena (Elo 1310), based on human preference on image-understanding tasks.

    Best when: Consider only after reviewing the cited caution.

  3. 03

    DeepSeek: DeepSeek V4 Flash Vision Exp

    DeepSeek V4 Flash Vision Exp is an experimental open-weight vision model with documented API support for base64 data URLs, external URLs, and file IDs, plus reported production latency of 9–13 seconds per successful visual qualification call.

    Best when: Use when you need an open-weight option with flexible image input methods including base64 data URLs for screenshots or direct file uploads via the Files API.

    Tips

    • Use when you need an open-weight option with flexible image input methods including base64 data URLs for screenshots or direct file uploads via the Files API.
      Source 1
      “## Resolution 研究完成（来源：官方图像理解指南 https://api-docs.deepseek.com/zh-cn/guides/vision + Tool Calls / 思考模式指南；**无任何 live 调用**）。完整契约见 `docs/research/vision-api-contract.md`（分支 `research/vision-api-contract`）。核心结论： - **模型**：`deepseek-v4-flash-vision-exp`（experimental，额外接受图像输入）。OpenAI 兼容 `/chat/completions`。 - **传图**：`content` 必须是**块数组**（非纯字符串）。三种方式——base64 data URL（`image_url` 块）、外链 URL（≤8192 字符，单图 ≤32 MiB，60s 内下载）、Files API `file_id`。扫雷棋盘建议走 base64 data URL。 - **`detail`**：`low`（512×512，更快/省）/ `high` /…”
      MiSmilerOpen original ↗
      Source 2
      “## Problem DeepSeek released its first multimodal vision model **`deepseek-v4-flash-vision-exp`** on 2026-08-21 (official announcement: https://api-docs.deepseek.com/news/news260821/). It is live on the DeepSeek API (verified: `GET https://api.deepseek.com/models` lists it, and chat completions with image input work). However, pi's built-in DeepSeek model catalog still only contains `deepseek-v4-flash` and `deepseek-v4-pro`. As a result, the new vision model does **not** appear in `/model` and…”
      phixz668-hubOpen original ↗
    • Deploy for latency-sensitive visual qualification pipelines where 9–13 second response times are acceptable and you want to avoid closed-weight dependencies.
      Source 3
      “## Objetivo Reducir el tiempo real de calificación, digitalización y generación de presentaciones sin sacrificar calidad, trazabilidad ni perder solicitudes en curso. ## Evidencia de producción (últimos 14 días) - Calificación completa: p50 157 s; p95 516 s. - Digitalización: p50 189 s. - Presentación reciente: 366 s. - DeepSeek V4 Flash Vision Exp en calificación visual: ~9–13 s por llamada exitosa. - Presentaciones con ese modelo: ~95 s por llamada y hasta tres llamadas por regeneración/revis…”
      Andres-backOpen original ↗

    Watch out for

    • Account for the experimental status and verify availability, as the model may not appear in all catalog listings despite being live on the DeepSeek API.
      Source 2
      “## Problem DeepSeek released its first multimodal vision model **`deepseek-v4-flash-vision-exp`** on 2026-08-21 (official announcement: https://api-docs.deepseek.com/news/news260821/). It is live on the DeepSeek API (verified: `GET https://api.deepseek.com/models` lists it, and chat completions with image input work). However, pi's built-in DeepSeek model catalog still only contains `deepseek-v4-flash` and `deepseek-v4-pro`. As a result, the new vision model does **not** appear in `/model` and…”
      phixz668-hubOpen original ↗

Sources

  1. 1

    “## Resolution 研究完成（来源：官方图像理解指南 https://api-docs.deepseek.com/zh-cn/guides/vision + Tool Calls / 思考模式指南；**无任何 live 调用**）。完整契约见 `docs/research/vision-api-contract.md`（分支 `research/vision-api-contract`）。核心结论： - **模型**：`deepseek-v4-flash-vision-exp`（experimental，额外接受图像输入）。OpenAI 兼容 `/chat/completions`。 - **传图**：`content` 必须是**块数组**（非纯字符串）。三种方式——base64 data URL（`image_url` 块）、外链 URL（≤8192 字符，单图 ≤32 MiB，60s 内下载）、Files API `file_id`。扫雷棋盘建议走 base64 data URL。 - **`detail`**：`low`（512×512，更快/省）/ `high` /…”

    MiSmiler · GitHub · Aug 24, 2026
  2. 2

    “## Problem DeepSeek released its first multimodal vision model **`deepseek-v4-flash-vision-exp`** on 2026-08-21 (official announcement: https://api-docs.deepseek.com/news/news260821/). It is live on the DeepSeek API (verified: `GET https://api.deepseek.com/models` lists it, and chat completions with image input work). However, pi's built-in DeepSeek model catalog still only contains `deepseek-v4-flash` and `deepseek-v4-pro`. As a result, the new vision model does **not** appear in `/model` and…”

    phixz668-hub · GitHub · Aug 24, 2026
  3. 3

    “## Objetivo Reducir el tiempo real de calificación, digitalización y generación de presentaciones sin sacrificar calidad, trazabilidad ni perder solicitudes en curso. ## Evidencia de producción (últimos 14 días) - Calificación completa: p50 157 s; p95 516 s. - Digitalización: p50 189 s. - Presentación reciente: 366 s. - DeepSeek V4 Flash Vision Exp en calificación visual: ~9–13 s por llamada exitosa. - Presentaciones con ese modelo: ~95 s por llamada y hasta tres llamadas por regeneración/revis…”

    Andres-back · GitHub · Sep 4, 2026

Rankings synthesized from community evidence and open benchmarks. See methodology. Not driven by vendor marketing.