MODEL CAPABILITY · PRICE & RELEASES

Value

Artificial Analysis · Compare benchmark results, text costs and release dates separately, with each model and configuration identified.

Data as of2026-10-26 · 64 configurations

Methodology & original report ↗

Value comparison

Index ≥30 · best-value configuration per developer · 3:1 input/output token mix.

Chart data · 10 entries
NameIndex / USD cost
Claude Haiku 5.5216.975
MiMo-V2.6-Flash216.482
GPT-6 Luna190.623
GLM-5.3-Flash176.031
Qwen3.8-Flash-Next173.14
MiniMax-M3.1-Flash162.689
Ling 3.1 Flash 101997.55
DeepSeek V4.1 Flash 101785.898
Beam 1.050.556
Step 5 Preview30.691

Input and output prices for the same models

Same configurations as the top 8 in the value chart · USD per million tokens · input and output billed separately.

InputOutput
Chart data · 8 entries
NameInput / output
Claude Haiku 5.50.1 / 0.5
MiMo-V2.6-Flash0.14 / 0.28
GPT-6 Luna0.1 / 0.5
GLM-5.3-Flash0.15 / 0.5
Qwen3.8-Flash-Next0.15 / 0.47
MiniMax-M3.1-Flash0.15 / 0.6
Ling 3.1 Flash 10190.3 / 0.9
DeepSeek V4.1 Flash 10170.3 / 1.2

ValueDetails

Sorted by value, with reasoning configurations kept separate. Requires a capability index of at least 30; text costs use a 3:1 input/output mix.

On this page20records
  1. 1

    Claude Haiku 5.5 (Max)

    Anthropic

    Capability index
    43.40
    Input / million tokens
    $0.1
    Output / million tokens
    $0.5
    Value · 3:1 usage mix
    217.0
  2. 2

    MiMo-V2.6-Flash

    Xiaomi

    Capability index
    37.88
    Input / million tokens
    $0.14
    Output / million tokens
    $0.28
    Value · 3:1 usage mix
    216.5
  3. 3

    Claude Haiku 5.5 (Xhigh)

    Anthropic

    Capability index
    41.25
    Input / million tokens
    $0.1
    Output / million tokens
    $0.5
    Value · 3:1 usage mix
    206.2
  4. 4

    GPT-6 Luna (Max)

    OpenAI

    Capability index
    38.12
    Input / million tokens
    $0.1
    Output / million tokens
    $0.5
    Value · 3:1 usage mix
    190.6
  5. 5

    Claude Haiku 5.5 (High)

    Anthropic

    Capability index
    37.82
    Input / million tokens
    $0.1
    Output / million tokens
    $0.5
    Value · 3:1 usage mix
    189.1
  6. 6

    GLM-5.3-Flash

    Z AI

    Capability index
    41.81
    Input / million tokens
    $0.15
    Output / million tokens
    $0.5
    Value · 3:1 usage mix
    176.0
  7. 7

    Qwen3.8-Flash-Next

    Alibaba

    Capability index
    39.82
    Input / million tokens
    $0.15
    Output / million tokens
    $0.47
    Value · 3:1 usage mix
    173.1
  8. 8

    GPT-6 Luna (Xhigh)

    OpenAI

    Capability index
    34.56
    Input / million tokens
    $0.1
    Output / million tokens
    $0.5
    Value · 3:1 usage mix
    172.8
  9. 9

    Claude Haiku 5.5 (Medium)

    Anthropic

    Capability index
    34.46
    Input / million tokens
    $0.1
    Output / million tokens
    $0.5
    Value · 3:1 usage mix
    172.3
  10. 10

    GPT-6 Luna (High)

    OpenAI

    Capability index
    32.93
    Input / million tokens
    $0.1
    Output / million tokens
    $0.5
    Value · 3:1 usage mix
    164.6
  11. 11

    MiniMax-M3.1-Flash

    MiniMax

    Capability index
    42.71
    Input / million tokens
    $0.15
    Output / million tokens
    $0.6
    Value · 3:1 usage mix
    162.7
  12. 12

    Ling 3.1 Flash 1019

    InclusionAI

    Capability index
    43.90
    Input / million tokens
    $0.3
    Output / million tokens
    $0.9
    Value · 3:1 usage mix
    97.5
  13. 13

    Ling 3.1 Flash

    InclusionAI

    Capability index
    41.09
    Input / million tokens
    $0.3
    Output / million tokens
    $0.9
    Value · 3:1 usage mix
    91.3
  14. 14

    DeepSeek V4.1 Flash 1017 (Max)

    DeepSeek

    Capability index
    45.10
    Input / million tokens
    $0.3
    Output / million tokens
    $1.2
    Value · 3:1 usage mix
    85.9
  15. 15

    MiMo-V2.6-Pro

    Xiaomi

    Capability index
    46.32
    Input / million tokens
    $0.435
    Output / million tokens
    $0.87
    Value · 3:1 usage mix
    85.2
  16. 16

    DeepSeek V4 Flash Vision (Max)

    DeepSeek

    Capability index
    34.84
    Input / million tokens
    $0.44
    Output / million tokens
    $1.32
    Value · 3:1 usage mix
    52.8
  17. 17

    Beam 1.0

    Reflection

    Capability index
    30.33
    Input / million tokens
    $0.4
    Output / million tokens
    $1.2
    Value · 3:1 usage mix
    50.6
  18. 18

    Step 5 Preview

    StepFun

    Capability index
    43.73
    Input / million tokens
    $1
    Output / million tokens
    $2.7
    Value · 3:1 usage mix
    30.7
  19. 19

    Qwen3.8 27B (Xhigh)

    Alibaba

    Capability index
    33.68
    Input / million tokens
    $0.5
    Output / million tokens
    $3
    Value · 3:1 usage mix
    29.9
  20. 20

    Gemini 3.8 Flash (High)

    Google

    Capability index
    40.93
    Input / million tokens
    $0.75
    Output / million tokens
    $3.75
    Value · 3:1 usage mix
    27.3
Ranking criteria & test conditions
  • Intelligence scores come from the same leaderboard snapshot. Reasoning configurations remain separate; estimated scores and retired models are excluded from the highlights.
  • Release dates follow the report and are separate from our update dates. Undated models are excluded from recent releases. A report’s date is not treated as independent proof of an official model release.
  • Text prices use USD per million tokens, with input and output stored separately. Subscription, cache and media charges are not mixed into this comparison.
  • Value picks require an intelligence score of at least 30 and rank by score ÷ (3 × input price + output price) × 4, selecting the highest value for each developer. This assumes a 3:1 text input/output ratio; actual task costs vary.
  • Developer highlights show one representative per developer. Model aliases and reasoning configurations are not automatically mapped to a specific catalog version. Full results retain the original configurations and missing values.

Charts are calculated from the full report, independently of the detail page. Release activity uses release dates, not changes in model capability over time. Missing prices are not zero costs.