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Ranking data as of

Best Value LLM for Coding in 2026 — Cost-Adjusted Rankings

As of November 13, 2026, the top model among value LLM for coding on the BenchLM leaderboard is Ministral 3 3B with a score of 282.2.

Bottom line: value here is coding score per output dollar, so check each row's raw score before you shortlist it.

Full Rankings (102 ranked)

1
Ministral 3 3B
Mistral·Open Weight·128K

282.2

Score/$

Score: 28.2 · $0.1/1M

vs #2
2
MiMo-V2.6-Flash
Xiaomi·Open Weight·1M

197.89

Score/$

Score: 55.4 · $0.28/1M

vs #3
3
Ministral 3 8B
Mistral·Open Weight·128K

194.13

Score/$

Score: 29.1 · $0.15/1M

vs #4
4
Ministral 3 14B
Mistral·Open Weight·128K

149.95

Score/$

Score: 30 · $0.2/1M

vs #5
5
Mercury 2.5
Inception·Proprietary·260K

134.33

Score/$

Score: 20.2 · $0.15/1M

vs #6
6
Claude Haiku 5.5
Anthropic·Proprietary·1M

117.86

Score/$

Score: 58.9 · $0.5/1M

vs #7
7
GPT-6 Luna
OpenAI·Proprietary·1.05M

104.1

Score/$

Score: 52.1 · $0.5/1M

vs #8
8
MiniMax M3.1 Flash
MiniMax·Proprietary·1M

88.67

Score/$

Score: 53.2 · $0.6/1M

vs #9
9
Qwen3.5 Flash
Alibaba·Proprietary·1M

72.8

Score/$

Score: 29.1 · $0.4/1M

vs #10
10
DeepSeek V3.2
DeepSeek·Open Weight·128K

70.5

Score/$

Score: 29.6 · $0.42/1M

vs #11
11
MiMo-V2.6-Pro
Xiaomi·Open Weight·1M

64.28

Score/$

Score: 55.9 · $0.87/1M

vs #12
12
Inkling 2 Small
Thinking Machines Lab·Proprietary·1M

57.44

Score/$

Score: 57.4 · $1/1M

vs #13
13
DeepSeek V4.1 Flash 1017
DeepSeek·Open Weight·1M

49.74

Score/$

Score: 59.7 · $1.2/1M

vs #14
14
GPT-5.6 Luna
OpenAI·Proprietary·1.05M

48.01

Score/$

Score: 57.6 · $1.2/1M

vs #15
15
MiniMax M3
MiniMax·Open Weight·1M

31.62

Score/$

Score: 37.9 · $1.2/1M

vs #16
16
MiniMax M2.7
MiniMax·Open Weight·200K

29.7

Score/$

Score: 35.6 · $1.2/1M

vs #17
17
MiniMax M2.5
MiniMax·Proprietary·128K

29.09

Score/$

Score: 34.9 · $1.2/1M

vs #18
18
Step 3.7 Flash
StepFun·Open Weight·256K

28.66

Score/$

Score: 33 · $1.15/1M

vs #19
19
GPT-4.1 nano
OpenAI·Proprietary·1M

27.6

Score/$

Score: 11 · $0.4/1M

vs #20
20
Inkling-Small
Thinking Machines Lab·Open Weight·1M

26.03

Score/$

Score: 37.5 · $1.44/1M

vs #21
21
Celeris-1
Celeris·Proprietary·128K

25.17

Score/$

Score: 17.6 · $0.7/1M

vs #22
22
Quasar 438B
Multiverse Computing·Proprietary·1M

24.57

Score/$

Score: 44.2 · $1.8/1M

vs #23
23
GPT-5.4 nano
OpenAI·Proprietary·400K

24.49

Score/$

Score: 30.6 · $1.25/1M

vs #24
24
Mistral Small 4
Mistral·Open Weight·256K

22.7

Score/$

Score: 13.6 · $0.6/1M

vs #25
25
Mistral Large 4
Mistral·Open Weight·1M

20.96

Score/$

Score: 44 · $2.1/1M

vs #26
26
Mercury 2
Inception·Proprietary·128K

20.81

Score/$

Score: 15.6 · $0.75/1M

vs #27
27
Trinity-Large-Thinking
Arcee AI·Open Weight·512K

20.62

Score/$

Score: 18.6 · $0.9/1M

vs #28
28
Gemini 3.1 Flash-Lite
Google·Proprietary·1M

19.27

Score/$

Score: 28.9 · $1.5/1M

vs #29
29
Step 5 Preview
StepFun·Open Weight·1M

18.16

Score/$

Score: 49 · $2.7/1M

vs #30
30
DeepSeek V3
DeepSeek·Open Weight·128K

15.15

Score/$

Score: 16.7 · $1.1/1M

vs #31
31
DeepSeek V3.2 (Thinking)
DeepSeek·Open Weight·128K

14.85

Score/$

Score: 32.5 · $2.19/1M

vs #32
32
Gemini 3.8 Flash
Google·Proprietary·1M

14.73

Score/$

Score: 55.3 · $3.75/1M

vs #33
33
Gemini 3.7 Flash
Google·Proprietary·1M

14.58

Score/$

Score: 54.7 · $3.75/1M

vs #34
34
GPT-5 mini
OpenAI·Proprietary·128K

14.03

Score/$

Score: 28.1 · $2/1M

vs #35
35
GPT-6.1 Terra
OpenAI·Proprietary·1.05M

13.96

Score/$

Score: 69.8 · $5/1M

vs #36
36
Gemini 3.5 Flash-Lite
Google·Proprietary·1M

13.87

Score/$

Score: 34.7 · $2.5/1M

vs #37
37
Gemini 3.6 Flash
Google·Proprietary·1M

13.54

Score/$

Score: 50.8 · $3.75/1M

vs #38
38
Grok Build 0.1
xAI·Proprietary·256K

13.42

Score/$

Score: 26.8 · $2/1M

vs #39
39
GPT-4o mini
OpenAI·Proprietary·128K

13.37

Score/$

Score: 8 · $0.6/1M

vs #40
40
Kimi K2.5
Moonshot AI·Open Weight·256K

13.13

Score/$

Score: 39.4 · $3/1M

vs #41
41
Grok Code Fast 1
xAI·Proprietary·256K

12.69

Score/$

Score: 19 · $1.5/1M

vs #42
42
GLM-5
Z.AI·Open Weight·200K

12.08

Score/$

Score: 38.7 · $3.2/1M

vs #43
43
GLM-5.2
Z.AI·Open Weight·1M

11.84

Score/$

Score: 52.1 · $4.4/1M

vs #44
44
Muse Spark 1.2
Meta·Proprietary·1M

11.77

Score/$

Score: 50 · $4.25/1M

vs #45
45
DeepSeek V4 Pro 0813
DeepSeek·Open Weight·1M

11.72

Score/$

Score: 46.4 · $3.96/1M

vs #46
46
Kimi K2.5 (Reasoning)
Moonshot AI·Open Weight·128K

11.56

Score/$

Score: 34.7 · $3/1M

vs #47
47
Gemini 3 Flash
Google·Proprietary·1M

10.83

Score/$

Score: 32.5 · $3/1M

vs #48
48
Kimi K2.6
Moonshot AI·Open Weight·256K

10.76

Score/$

Score: 43 · $4/1M

vs #49
49
GPT-4.1 mini
OpenAI·Proprietary·1M

10.68

Score/$

Score: 17.1 · $1.6/1M

vs #50
50
Grok 4.3
xAI·Proprietary·1M

10.65

Score/$

Score: 26.6 · $2.5/1M

vs #51
51
GLM-5.1
Z.AI·Open Weight·203K

10.49

Score/$

Score: 46.2 · $4.4/1M

vs #52
52
Mistral Large 3
Mistral·Open Weight·128K

10.48

Score/$

Score: 15.7 · $1.5/1M

vs #53
53
Kimi K2.7 Code
Moonshot AI·Open Weight·256K

10.44

Score/$

Score: 41.8 · $4/1M

vs #54
54
Gemini 4 Hydrogen
Google·Proprietary·1M

10.1

Score/$

Score: 75.8 · $7.5/1M

vs #55
55
Grok 4.20
xAI·Proprietary·2M

9.72

Score/$

Score: 24.3 · $2.5/1M

vs #56
56
Grok 4.6
xAI·Proprietary·500K

9.09

Score/$

Score: 54.6 · $6/1M

vs #57
57
Gemini 4 Carbon
Google·Proprietary·1M

8.39

Score/$

Score: 83.9 · $10/1M

vs #58
58
GLM-5V-Turbo
Z.AI·Proprietary·200K

8.32

Score/$

Score: 33.3 · $4/1M

vs #59
59
Grok 4.5
xAI·Proprietary·500K

8.14

Score/$

Score: 48.9 · $6/1M

vs #60
60
Claude Sonnet 5.5
Anthropic·Proprietary·1M

8.1

Score/$

Score: 81 · $10/1M

vs #61
61
GPT-5.4 mini
OpenAI·Proprietary·400K

7.55

Score/$

Score: 34 · $4.5/1M

vs #62
62
Inkling
Thinking Machines Lab·Open Weight·1M

7.49

Score/$

Score: 35.1 · $4.68/1M

vs #63
63
GPT-6.1 Sol
OpenAI·Proprietary·1.05M

7.34

Score/$

Score: 73.4 · $10/1M

vs #64
64
Gemini 4 Argon
Google·Proprietary·1M

7.18

Score/$

Score: 71.8 · $10/1M

vs #65
65
GPT-6 Sol
OpenAI·Proprietary·1.05M

6.73

Score/$

Score: 67.3 · $10/1M

vs #66
66
Kimi K3.1 Pro
Moonshot AI·Open Weight·1.05M

6.1

Score/$

Score: 61 · $10/1M

vs #67
67
Gemini 3.5 Flash
Google·Proprietary·1M

5.56

Score/$

Score: 50.1 · $9/1M

vs #68
68
Claude Sonnet 5
Anthropic·Proprietary·1M

5.16

Score/$

Score: 51.6 · $10/1M

vs #69
69
GPT-5.6 Terra
OpenAI·Proprietary·1.05M

4.76

Score/$

Score: 57.1 · $12/1M

vs #70
70
Claude Haiku 4.5
Anthropic·Proprietary·200K

4.67

Score/$

Score: 23.3 · $5/1M

vs #71
71
Claude Opus 5.5
Anthropic·Proprietary·1M

4.13

Score/$

Score: 82.6 · $20/1M

vs #72
72
GPT-5.1
OpenAI·Proprietary·200K

3.78

Score/$

Score: 37.8 · $10/1M

vs #73
73
Kimi K3
Moonshot AI·Open Weight·1.05M

3.74

Score/$

Score: 56.2 · $15/1M

vs #74
74
GPT-5.3 Codex
OpenAI·Proprietary·400K

3.69

Score/$

Score: 51.7 · $14/1M

vs #75
75
GPT-5.1-Codex
OpenAI·Proprietary·400K

3.63

Score/$

Score: 36.3 · $10/1M

vs #76
76
Gemini 3 Pro
Google·Proprietary·2M

3.61

Score/$

Score: 43.3 · $12/1M

vs #77
77
Gemini 1.5 Pro
Google·Proprietary·2M

3.29

Score/$

Score: 16.5 · $5/1M

vs #78
78
GPT-5.4
OpenAI·Proprietary·1.05M

3.25

Score/$

Score: 48.8 · $15/1M

vs #79
79
Muse Wonder
Meta·Proprietary·1M

3.25

Score/$

Score: 64.9 · $20/1M

vs #80
80
GPT-5.2-Codex
OpenAI·Proprietary·400K

3.22

Score/$

Score: 45 · $14/1M

vs #81
81
Gemini 3.1 Pro
Google·Proprietary·1M

3.16

Score/$

Score: 37.9 · $12/1M

vs #82
82
GPT-5.6 Sol
OpenAI·Proprietary·1.05M

3.12

Score/$

Score: 62.4 · $20/1M

vs #83
83
Claude Sonnet 4.6
Anthropic·Proprietary·200K

2.98

Score/$

Score: 44.7 · $15/1M

vs #84
84
GPT-5.2
OpenAI·Proprietary·400K

2.71

Score/$

Score: 37.9 · $14/1M

vs #85
85
Claude Opus 5
Anthropic·Proprietary·

2.67

Score/$

Score: 66.8 · $25/1M

vs #86
86
Mistral Medium 3.5 128B
Mistral·Open Weight·256K

2.6

Score/$

Score: 19.5 · $7.5/1M

vs #87
87
Claude Opus 4.8
Anthropic·Proprietary·1M

2.23

Score/$

Score: 55.7 · $25/1M

vs #88
88
Claude Fable 5.2
Anthropic·Proprietary·1M

2.23

Score/$

Score: 89.2 · $40/1M

vs #89
89
Gemini 2.5 Pro
Google·Proprietary·1M

2.19

Score/$

Score: 21.9 · $10/1M

vs #90
90
Claude Opus 4.7 (Adaptive)
Anthropic·Proprietary·1M

2.15

Score/$

Score: 53.8 · $25/1M

vs #91
91
Claude Opus 4.7
Anthropic·Proprietary·1M

2.14

Score/$

Score: 53.6 · $25/1M

vs #92
92
GPT-5.5
OpenAI·Proprietary·1M

1.92

Score/$

Score: 57.7 · $30/1M

vs #93
93
Claude Opus 4.6
Anthropic·Proprietary·1M

1.84

Score/$

Score: 46 · $25/1M

vs #94
94
Claude Opus 4.5
Anthropic·Proprietary·200K

1.75

Score/$

Score: 43.6 · $25/1M

vs #95
95
GPT-6 Astra
OpenAI·Proprietary·1.05M

1.57

Score/$

Score: 78.7 · $50/1M

vs #96
96
Command A+
Cohere·Open Weight·128K

1.57

Score/$

Score: 15.7 · $10/1M

vs #97
97
Claude Fable 5.1
Anthropic·Proprietary·1M

1.48

Score/$

Score: 73.9 · $50/1M

vs #98
98
Claude Fable 5
Anthropic·Proprietary·1M+

1.35

Score/$

Score: 67.7 · $50/1M

vs #99
99
o1
OpenAI·Proprietary·200K

0.44

Score/$

Score: 26.3 · $60/1M

vs #100
100
GPT-4 Turbo
OpenAI·Proprietary·128K

0.4

Score/$

Score: 11.9 · $30/1M

vs #101
101
o1-preview
OpenAI·Proprietary·200K

0.36

Score/$

Score: 21.9 · $60/1M

vs #102
102
Claude 3 Opus
Anthropic·Proprietary·200K

0.17

Score/$

Score: 12.6 · $75/1M

How to choose

Key Takeaways

The best value model is Ministral 3 3B by Mistral with a provisional Score/$ ratio of 282.2 (score: 28.2, output: $0.1/1M tokens).

The best open-weight model is Ministral 3 3B at position #1.

102 models are included in this ranking.

Score in Context

What these scores mean

Value scores divide the weighted coding score by output token price (per 1M tokens). Higher means more capability per dollar. Models with no listed price are excluded.

Known limitations

Value rankings favor cheap models even if absolute performance is modest. A model scoring half as well at one-tenth the price wins on value — but may not meet your quality bar. Always check raw scores alongside value rankings.

About this ranking

Ranking data as of November 13, 2026

Raw benchmark scores only tell half the story. This ranking divides each model's weighted coding score by its output token price, surfacing models that deliver the most coding capability per dollar spent. A model scoring 70 at $1/1M tokens outranks one scoring 80 at $15/1M tokens here — because for the same budget you get far more coding work done. Use this alongside the standard coding leaderboard to find the sweet spot between performance and cost for your coding workflows.

For a browser interface or a small web app, use the frontend model shortlist and test the generated UI before accepting it.

Unless noted otherwise, ranking surfaces on this page use BenchLM’s provisional leaderboard lane rather than the stricter sourced-only verified leaderboard.

Ministral 3 3B leads this ranking with a score of 282.2, followed by MiMo-V2.6-Flash (197.89) and Ministral 3 8B (194.13). There is a significant gap between the leading models and the rest of the field.

The best open-weight option is Ministral 3 3B (ranked #1 with a score of 282.2). Open-weight models are highly competitive in this category — self-hosting is a viable alternative to proprietary APIs.

This ranking uses provisional weighted averages across the scoring benchmarks in coding. For detailed model profiles, click any model name above. To compare two specific models head-to-head, use the "vs #" links.

Questions

What is the best LLM for coding right now?

For raw coding capability, use the live coding leaderboard — it recomputes the order from calibrated coding evidence on every build, with evidence labels showing which positions are Supported versus Estimated. This page answers the follow-up question: which model delivers the most coding capability per dollar spent.

Is Claude or GPT better for coding?

The live coding leaderboard reflects the latest results. Evidence labels matter as much as rank: a Supported position slightly below an Estimated one is often the safer pick for production coding work.

What is the best open-source LLM for coding?

Use the open-weight rows on the coding leaderboard for capability order, and the open-source rankings for the full downloadable-weights picture. Open coding leaders trail the proprietary top tier on raw score but often win decisively on this page’s capability-per-dollar measure.

Which coding model gives the best value?

That is what this ranking measures: weighted coding score divided by output token price. A cheap model with a low coding score can rank high here, so read each row's raw coding score next to its price before you shortlist it.

Know when it’s worth switching models

The model to choose, the cheaper alternative, and the release we would wait on.

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