Part of Best LLM for Structured Data Extraction

Best LLM for JSON & Schema Output

DeepSeek V4.1 Flash ranks first for JSON & Schema Output as of October 20, 2026.[1][2] It scores 79.25% on LiveBench Data Analysis (#14 of 59), including table joining and reformatting tasks. GPT-6.1 Sol is the next-ranked alternative. It scores 82.66% on LiveBench Data Analysis (#2 of 59), including table joining and reformatting tasks.

About this recommendation

Updated
Evidence through
Sources
8
Revision
v110

Decision audit

Why this result

Inspect the inputs and the computed order behind the recommendation.

Models screened

24

live candidates

Evaluation feeds

5

task-weighted

Winner coverage

42%

intended feed weight

Largest provider share

2 of 8

OpenAI

Established source breadth. 2 citation families and 0 practitioner families provide attributed capability reports; 0 cautionary threads retained. The largest citation family contributes 75%.

DeepSeek: DeepSeek V4.1 Flash leads the measured task comparison with 2 independent evaluation families. Community volume, release age and usage popularity add no ranking points. This category also weights its stated price or context criteria.

Real-world track record is still developing. The recommendation can lead on independent measurements while practitioner reports accumulate.

Sources evaluated

These are the weights used in scoring. Missing measurements are omitted from each model’s average. A feed with no result for any model released in the last 60 days is stale and does not score until it catches up.

winner: DeepSeek V4.1 Flash
Evaluation feedWeightWinner resultField measured
Structured-output evaldisabled; last successful check unknownunavailable
0%
feed unavailable0/24
LiveBench Data Analysis (2026-06-25)Observed 2026-10-18 · evaluation date not supplied · deepseek-v4.1-flash-maxfailing; last successful check 2026-10-18
50%
#1424/24
Berkeley Function Callingstale
0%
no current result0/24
LMArena TextObserved 2026-10-15 · evaluation date not supplied · deepseek-v4.1-flash-max
25%
#2624/24
price weight
25%
80/10024/24

Provider concentration

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

OpenAI25%
  • OpenAI2 models
  • Anthropic1 model
  • deepseek1 model
  • Meta1 model
  • Moonshot AI1 model
  • Qwen1 model
  • Z.ai1 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.

  1. 01DeepSeek V4.1 Flash86

    deepseek · coverage 42%

    #14 LiveBench Data Analysis · #26 LMArena Text

  2. 02GPT-6.1 Sol83

    OpenAI · coverage 42%

    #2 LiveBench Data Analysis · #17 LMArena Text

  3. 03Kimi K383

    Moonshot AI · coverage 42%

    #14 LMArena Text · #16 LiveBench Data Analysis

  4. 04GLM 5.3 Flash82

    Z.ai · coverage 42%

    #27 LiveBench Data Analysis · #29 LMArena Text

  5. 05Qwen3.8 27B80

    Qwen · coverage 42%

    #24 LiveBench Data Analysis · #64 LMArena Text

  6. 06Muse Spark 1.380

    Meta · coverage 42%

    #9 LiveBench Data Analysis · #9 LMArena Text

  7. 07GPT-6 Astra79

    OpenAI · coverage 42%

    #1 LiveBench Data Analysis · #23 LMArena Text

  8. 08Claude Opus 5.579

    Anthropic · coverage 42%

    #3 LMArena Text · #6 LiveBench Data Analysis

Task score averages the available, task-weighted measurements. Benchmark positions compare models matched to our catalog. Models measured by at least two independent evaluator families are considered first. Missing tests, practitioner report counts, popularity and release age add no points. Coverage describes evidence breadth, not a probability of correctness. Scores within two points are shown as close under this policy; this is not a statistical confidence interval. When the leading scores are that close, the model measured by more evaluator families ranks first.

  1. 01

    DeepSeek V4.1 Flashdeepseek · $0.056 in / $0.12 out per M tokens · 1.0M context · open-weight

    DeepSeek V4.1 Flash scores 79.25% on LiveBench Data Analysis (#14 of 59), including table joining and reformatting tasks.

    Best when: Its strongest result for this task is on LiveBench Data Analysis, which measures working with tables and structured data.
    Source 1
    “Within the 59 catalog models matched to this evaluation: Scores 79.25% on LiveBench Data Analysis (#14 of 59), including table joining and reformatting tasks.”
    LiveBench Data AnalysisOpen original ↗

    No practitioner reports are linked yet, so no cautions are listed. Absence of reports is not evidence of reliability.

  2. 02

    GPT-6.1 SolOpenAI · $2 in / $10 out per M tokens · 1.1M context

    GPT-6.1 Sol scores 82.66% on LiveBench Data Analysis (#2 of 59), including table joining and reformatting tasks.

    Best when: Its strongest result for this task is on LiveBench Data Analysis, which measures working with tables and structured data.
    Source 2
    “Within the 59 catalog models matched to this evaluation: Scores 82.66% on LiveBench Data Analysis (#2 of 59), including table joining and reformatting tasks.”
    LiveBench Data AnalysisOpen original ↗

    No practitioner reports are linked yet, so no cautions are listed. Absence of reports is not evidence of reliability.

  3. 03

    Kimi K3Moonshot AI · $0.24 in / $11.94 out per M tokens · 1.0M context · open-weight

    Kimi K3 ranks #14 of 152 on LMArena's overall text arena (Elo 1487), based on blind human preference votes.

    Best when: Its strongest result for this task is on LMArena Text, which measures general reasoning and instruction following.
    Source 3
    “Within the 152 catalog models matched to this evaluation: Ranks #14 of 152 on LMArena's overall text arena (Elo 1487), based on blind human preference votes.”
    LMArena text arenaOpen original ↗

    No practitioner reports are linked yet, so no cautions are listed. Absence of reports is not evidence of reliability.

  4. 04

    GLM 5.3 FlashZ.ai · $0.047 in / $0.16 out per M tokens · 1.0M context · open-weight

    GLM 5.3 Flash scores 76.4% on LiveBench Data Analysis (#27 of 59), including table joining and reformatting tasks.

    Best when: Its strongest result for this task is on LiveBench Data Analysis, which measures working with tables and structured data.
    Source 4
    “Within the 59 catalog models matched to this evaluation: Scores 76.4% on LiveBench Data Analysis (#27 of 59), including table joining and reformatting tasks.”
    LiveBench Data AnalysisOpen original ↗
  5. 05

    Qwen3.8 27BQwen · $0.040 in / $1.35 out per M tokens · 1M context · open-weight

    Qwen3.8 27B scores 76.59% on LiveBench Data Analysis (#24 of 59), including table joining and reformatting tasks.

    Best when: Its strongest result for this task is on LiveBench Data Analysis, which measures working with tables and structured data.
    Source 5
    “Within the 59 catalog models matched to this evaluation: Scores 76.59% on LiveBench Data Analysis (#24 of 59), including table joining and reformatting tasks.”
    LiveBench Data AnalysisOpen original ↗

    No practitioner reports are linked yet, so no cautions are listed. Absence of reports is not evidence of reliability.

  6. 06

    Muse Spark 1.3Meta · $1.25 in / $4.25 out per M tokens · 1.0M context

    Muse Spark 1.3 scores 79.57% on LiveBench Data Analysis (#9 of 59), including table joining and reformatting tasks.

    Best when: Its strongest result for this task is on LiveBench Data Analysis, which measures working with tables and structured data.
    Source 6
    “Within the 59 catalog models matched to this evaluation: Scores 79.57% on LiveBench Data Analysis (#9 of 59), including table joining and reformatting tasks.”
    LiveBench Data AnalysisOpen original ↗

    No practitioner reports are linked yet, so no cautions are listed. Absence of reports is not evidence of reliability.

  7. 07

    GPT-6 AstraOpenAI · $10 in / $50 out per M tokens · 1.1M context

    GPT-6 Astra scores 82.97% on LiveBench Data Analysis (#1 of 59), including table joining and reformatting tasks.

    Best when: Its strongest result for this task is on LiveBench Data Analysis, which measures working with tables and structured data.
    Source 7
    “Within the 59 catalog models matched to this evaluation: Scores 82.97% on LiveBench Data Analysis (#1 of 59), including table joining and reformatting tasks.”
    LiveBench Data AnalysisOpen original ↗

    No practitioner reports are linked yet, so no cautions are listed. Absence of reports is not evidence of reliability.

  8. 08

    Claude Opus 5.5Anthropic · $4 in / $20 out per M tokens · 1M context

    Claude Opus 5.5 ranks #3 of 152 on LMArena's overall text arena (Elo 1508), based on blind human preference votes.

    Best when: Its strongest result for this task is on LMArena Text, which measures general reasoning and instruction following.
    Source 8
    “Within the 152 catalog models matched to this evaluation: Ranks #3 of 152 on LMArena's overall text arena (Elo 1508), based on blind human preference votes.”
    LMArena text arenaOpen original ↗

    No practitioner reports are linked yet, so no cautions are listed. Absence of reports is not evidence of reliability.

Frequently asked

What is the best model for JSON & Schema Output?
DeepSeek V4.1 Flash ranks first as of October 20, 2026. DeepSeek V4.1 Flash scores 79.25% on LiveBench Data Analysis (#14 of 59), including table joining and reformatting tasks.[1]
What is the best alternative to DeepSeek V4.1 Flash?
GPT-6.1 Sol ranks second. GPT-6.1 Sol scores 82.66% on LiveBench Data Analysis (#2 of 59), including table joining and reformatting tasks.[2]
Can I self-host the top pick for JSON & Schema Output?
Yes. DeepSeek V4.1 Flash is open-weight, so it can run on your own hardware as well as through hosted routes.[1]

Sources

  1. 1

    “Within the 59 catalog models matched to this evaluation: Scores 79.25% on LiveBench Data Analysis (#14 of 59), including table joining and reformatting tasks.”

    LiveBench Data Analysis · Benchmark · Oct 18, 2026
  2. 2

    “Within the 59 catalog models matched to this evaluation: Scores 82.66% on LiveBench Data Analysis (#2 of 59), including table joining and reformatting tasks.”

    LiveBench Data Analysis · Benchmark · Oct 18, 2026
  3. 3

    “Within the 152 catalog models matched to this evaluation: Ranks #14 of 152 on LMArena's overall text arena (Elo 1487), based on blind human preference votes.”

    LMArena text arena · Benchmark · Oct 15, 2026
  4. 4

    “Within the 59 catalog models matched to this evaluation: Scores 76.4% on LiveBench Data Analysis (#27 of 59), including table joining and reformatting tasks.”

    LiveBench Data Analysis · Benchmark · Oct 18, 2026
  5. 5

    “Within the 59 catalog models matched to this evaluation: Scores 76.59% on LiveBench Data Analysis (#24 of 59), including table joining and reformatting tasks.”

    LiveBench Data Analysis · Benchmark · Oct 18, 2026
  6. 6

    “Within the 59 catalog models matched to this evaluation: Scores 79.57% on LiveBench Data Analysis (#9 of 59), including table joining and reformatting tasks.”

    LiveBench Data Analysis · Benchmark · Oct 18, 2026
  7. 7

    “Within the 59 catalog models matched to this evaluation: Scores 82.97% on LiveBench Data Analysis (#1 of 59), including table joining and reformatting tasks.”

    LiveBench Data Analysis · Benchmark · Oct 18, 2026
  8. 8

    “Within the 152 catalog models matched to this evaluation: Ranks #3 of 152 on LMArena's overall text arena (Elo 1508), based on blind human preference votes.”

    LMArena text arena · Benchmark · Oct 15, 2026

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