Part of Best LLM for Structured Data Extraction
Best LLM for High-Volume Extraction
DeepSeek V4.1 Flash is the provisional first pick for High-Volume Extraction as of October 21, 2026, while independent task measurements are still limited.[1][2] It scores 79.25% on LiveBench Data Analysis (#14 of 59), including table joining and reformatting tasks. Qwen3.8 27B is the next-ranked alternative. It scores 76.59% on LiveBench Data Analysis (#24 of 59), including table joining and reformatting tasks.
About this recommendation
- Updated
- Evidence through
- Sources
- 8
- Revision
- v105
Decision audit
Why this result
Inspect the inputs and the computed order behind the recommendation.
Models screened
24
live candidates
Evaluation feeds
4
task-weighted
Winner coverage
39%
intended feed weight
Largest provider share
3 of 8
deepseek
DeepSeek: DeepSeek V4.1 Flash leads the measured task comparison with limited independent task measurements. 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.
| Evaluation feed | Weight | Winner result | Field measured |
|---|---|---|---|
| Structured-output evaldisabled; last successful check unknownunavailable | 0% | feed unavailable | 0/24 |
| Route reliabilitydisabled; last successful check unknownunavailable | 0% | feed unavailable | 0/24 |
| price weight | 57% | 82/100 | 24/24 |
| 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 | 43% | #14 | 24/24 |
Provider concentration
Each exact model is scored separately; provider identity is not a ranking input.
- deepseek3 models
- Z.ai2 models
- Moonshot AI1 model
- OpenAI1 model
- Qwen1 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.
deepseek · coverage 39% · provisional evidence
#14 LiveBench Data Analysis
Qwen · coverage 39% · provisional evidence
#24 LiveBench Data Analysis
Z.ai · coverage 39% · provisional evidence
#27 LiveBench Data Analysis
Z.ai · coverage 39% · provisional evidence
#33 LiveBench Data Analysis
deepseek · coverage 39% · provisional evidence
#10 LiveBench Data Analysis
Moonshot AI · coverage 39% · provisional evidence
#16 LiveBench Data Analysis
OpenAI · coverage 39% · provisional evidence
#34 LiveBench Data Analysis
deepseek · coverage 39% · provisional evidence
#11 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.
- 01
DeepSeek V4.1 Flashdeepseek · $0.049 in / $0.38 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.No practitioner reports are linked yet, so no cautions are listed. Absence of reports is not evidence of reliability.
- 02
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.No practitioner reports are linked yet, so no cautions are listed. Absence of reports is not evidence of reliability.
- 03
GLM 5.3 FlashZ.ai · $0.041 in / $0.12 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.No practitioner reports are linked yet, so no cautions are listed. Absence of reports is not evidence of reliability.
- 04
GLM 5.2Z.ai · $0.034 in / $7 out per M tokens · 1.0M context · open-weight
GLM 5.2 scores 73.74% on LiveBench Data Analysis (#33 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.No practitioner reports are linked yet, so no cautions are listed. Absence of reports is not evidence of reliability.
- 05
DeepSeek V4 Flash Vision Expdeepseek · $0.22 in / $0.65 out per M tokens · 1.0M context · open-weight
DeepSeek V4 Flash Vision Exp scores 79.48% on LiveBench Data Analysis (#10 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.No practitioner reports are linked yet, so no cautions are listed. Absence of reports is not evidence of reliability.
- 06
Kimi K3Moonshot AI · $0.24 in / $11.94 out per M tokens · 1.0M context · open-weight
Kimi K3 scores 78.73% on LiveBench Data Analysis (#16 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.No practitioner reports are linked yet, so no cautions are listed. Absence of reports is not evidence of reliability.
- 07
GPT-6 LunaOpenAI · $0.100 in / $0.50 out per M tokens · 1.1M context
GPT-6 Luna scores 73.37% on LiveBench Data Analysis (#34 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.No practitioner reports are linked yet, so no cautions are listed. Absence of reports is not evidence of reliability.
- 08
DeepSeek V4 Flash 0731deepseek · $0.44 in / $1.32 out per M tokens · 1.0M context · open-weight
DeepSeek V4 Flash 0731 scores 79.33% on LiveBench Data Analysis (#11 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.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 High-Volume Extraction?
- DeepSeek V4.1 Flash ranks first as of October 21, 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?
- Qwen3.8 27B ranks second. Qwen3.8 27B scores 76.59% on LiveBench Data Analysis (#24 of 59), including table joining and reformatting tasks.[2]
- Can I self-host the top pick for High-Volume Extraction?
- 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
“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
“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 - 3
“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 - 4
“Within the 59 catalog models matched to this evaluation: Scores 73.74% on LiveBench Data Analysis (#33 of 59), including table joining and reformatting tasks.”
LiveBench Data Analysis · Benchmark · Oct 18, 2026 - 5
“Within the 59 catalog models matched to this evaluation: Scores 79.48% on LiveBench Data Analysis (#10 of 59), including table joining and reformatting tasks.”
LiveBench Data Analysis · Benchmark · Oct 18, 2026 - 6
“Within the 59 catalog models matched to this evaluation: Scores 78.73% on LiveBench Data Analysis (#16 of 59), including table joining and reformatting tasks.”
LiveBench Data Analysis · Benchmark · Oct 18, 2026 - 7
“Within the 59 catalog models matched to this evaluation: Scores 73.37% on LiveBench Data Analysis (#34 of 59), including table joining and reformatting tasks.”
LiveBench Data Analysis · Benchmark · Oct 18, 2026 - 8
“Within the 59 catalog models matched to this evaluation: Scores 79.33% on LiveBench Data Analysis (#11 of 59), including table joining and reformatting tasks.”
LiveBench Data Analysis · Benchmark · Oct 18, 2026
Rankings synthesized from community evidence and open benchmarks. See methodology. Not driven by vendor marketing.