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Interactive leaderboard

Interactive LLM Leaderboard 2026: Compare AI Models, API Cost & ROI

Compare 350+ LLMs in 2026: live API pricing, ROI scores, coding, reasoning, speed, and context. Built for teams in the US, Canada, and Australia evaluating OpenAI, Anthropic, Google Gemini, and open-weight models.

Why teams use this live LLM comparison table in 2026

This leaderboard blends normalized benchmarks with transparent estimated monthly API spend so you can shortlist models fast. Whether you procure from the United States, Canada, or Australia, you get one place to compare flagship chat models, long-context SKUs, and cost-optimized tiers—then jump into comparisons or embed the same data on your site.

Est. monthlyROI scoreCodingReasoningSpeedMathContextOverallOpen-weight

Workload & pricing toggles

Workload presets

Same three scenarios as the main AI API calculator: moderate traffic, large RAG-style context, or per-request max tokens with a lower request count.

Include Vision / Image Processing

Off — no image fees in cost estimates for vision-capable models.

Turn On to include image fees.

OffOn

Use Cached Pricing

Enable to get 50% off input tokens where cached rates apply

OffOn

Deep Reasoning / Thinking Mode

Model hidden reasoning / extended thinking charged like output tokens when enabled.

OffOn

Batch Pricing

Enable for 50% off input & output where batch/async pricing applies

OffOn
≈ $100.00/mo
8K
1K—1.0M
≈ $100.00/mo
2K
100—500K
≈ $200.00 total
5K
10—100K

Cached / batch est. monthly values only change after the pipeline sets supports_caching or supports_batch in Supabase. The toggles here narrow the table to models whose catalog or provider typically supports those modes.

Magic quadrant (top 15)

X: est. monthly · Y: Overall · Dot: provider color · Hover for rank, model & details

Full leaderboard

Showing 48 of 327 models.

PickModelEst. monthlyROI scoreCodingReasoningSpeedMathContextOverall
OpenAI: gpt-oss-20b$2.6084
96
97
85
98
131K
97
Grok 3$270.0061
93
93
55
96
131K
94
Google: Gemma 4 31B$9.0072
97
92
70
97
262K
94
Z.ai: GLM 5$44.8064
99
93
55
84
203K
92
Z.ai: GLM 4.7$32.6064
94
87
85
96
203K
91
Z.ai: GLM 5.1$77.0061
92
89
70
85
203K
89
Qwen: Qwen3.5 397B A17B$39.0062
85
89
60
92
262K
89
Qwen: Qwen3 32B$5.6073
85
89
60
92
41K
89
Qwen: Qwen3 Max$70.2061
93
87
70
89
262K
89
Mistral: Mistral Medium 3$36.0063
92
87
70
91
131K
89
Qwen: Qwen3.5-27B$23.4064
80
91
70
92
262K
88
Baidu: ERNIE 4.5 21B A3B$5.6072
85
89
60
87
120K
88
Qwen: Qwen3 VL 32B Instruct$8.3269
88
88
65
87
131K
88
Qwen: Qwen3.5-35B-A3B$19.5064
76
89
70
95
262K
87
AllenAI: Olmo 3 32B Think$11.0067
90
84
50
88
66K
87
Qwen: Qwen3.5-122B-A10B$31.2062
81
90
55
85
262K
87
Anthropic: Claude Opus 4.5$450.0057
85
84
55
95
200K
87
Upstage: Solar Pro 3$12.0066
85
89
65
80
128K
86
Amazon: Nova Premier 1.0$225.0057
89
89
55
77
1.0M
86
Xiaomi: MiMo-V2-Pro$70.0059
85
89
60
80
1.0M
86
Elephant
Free
78
90
83
70
88
262K
86
Anthropic: Claude Opus 4$1,350.0055
85
81
55
95
200K
86
Arcee AI: Trinity Large Thinking$17.3064
85
89
55
80
262K
86
Meta: Llama 3.3 70B Instruct$7.2069
88
89
70
77
131K
86
MoonshotAI: Kimi K2 0711$45.8060
90
87
60
80
131K
86
Deep Cogito: Cogito v2.1 671B$62.5059
85
89
60
80
128K
86
OpenAI: GPT-5.1 Chat$150.0058
91
88
85
77
128K
86
AionLabs: Aion-1.0-Mini$42.0061
85
85
95
88
131K
86
xAI: Grok 4.20$140.0057
88
87
55
76
2.0M
85
OpenAI: GPT-5.2$210.0057
85
89
65
78
400K
85
Claude Sonnet 4.6$270.0056
93
75
70
96
1.0M
85
Claude Opus 4.6$450.0056
85
79
55
95
1.0M
85
NVIDIA: Nemotron Nano 9B V2$3.2075
72
84
85
98
131K
85
OpenAI: GPT-5.1-Codex-Mini$30.0061
84
82
85
92
400K
85
OpenAI: GPT-5.5$500.0055
92
88
55
71
1.1M
85
xAI: Grok 3 Mini Beta$17.0063
90
87
95
77
131K
85
Z.ai: GLM 5V Turbo$88.0058
88
83
70
80
203K
84
xAI: Grok 3 Mini$17.0063
88
86
92
76
131K
84
DeepSeek: DeepSeek V4 Flash$8.4067
90
83
95
80
1.0M
84
Nous: Hermes 4 70B$9.2066
85
81
60
88
131K
84
Auto Router
VARIABLE
77
84
83
70
86
2.0M
84
Qwen: Qwen3 235B A22B Thinking 2507$20.9362
74
89
50
83
131K
84
GLM 5 Turbo$88.0057
88
91
70
60
203K
83
Tencent: Hunyuan A13B Instruct$11.3064
64
86
55
94
131K
83
xAI: Grok 4$270.0055
87
80
70
87
256K
83
Xiaomi: MiMo-V2.5-Pro$70.0057
78
78
70
95
1.0M
82
NVIDIA: Llama 3.3 Nemotron Super 49B V1.5$8.0066
74
79
70
97
131K
82
OpenAI: GPT-5.2 Pro$2,520.0052
85
85
55
73
400K
82

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How it works

Methodology: How we rank Overall LLMs

Transparent, benchmark-driven rankings—same craft as our single-model deep dives.

How overall scores and monthly estimates are combined

Overall rankings blend coding, reasoning, speed, math, and multimodal signals with transparent API pricing context. The composite reflects general-purpose fitness for teams that need one leaderboard to compare flagship models before deeper evaluations—whether you operate primarily in the US, Canada, or Australia.

Battle Arena

Compare up to four LLMs side by side

Tick up to four models in the leaderboard table, then open Battle Arena for API pricing, benchmarks, and workload math in one view—perfect when you are shortlisting vendors for a pilot in the US, Canada, or Australia.

Prefer a head start? Jump into high-intent comparisons people search for every day—same interactive calculator, zero signup.

Open Battle ArenaUp to 4 models · Live estimates
Signals & spend

Value analysis

Benchmarks vs. estimated API cost—read the story your CFO cares about.

Reading ROI and cost together on the overall view

Overall value is not “the highest benchmark score”—it is capability per dollar for a workload you define. Use workload sliders to mirror production traffic; when you enable batch or cached pricing, we only apply discounts our data marks as supported so finance teams in the US, Canada, and Australia can trust the directional spend story before they negotiate contracts.

Production deployment

Enterprise AI Deployment & Use Cases

How teams in the US, Canada, and Australia deploy these models in production.

Matching models to production RAG and multi-agent systems

Modern enterprise architectures rarely rely on a single model. Teams in the US and Canada frequently deploy a 'router' pattern: routing simple queries to fast, cost-optimized models while reserving frontier flagships for complex reasoning or code generation. This leaderboard helps you map out that multi-model strategy by identifying the best-in-class models for each specific capability tier.

Architecture

API Cost & Architecture Optimization

Strategies to reduce monthly API spend without sacrificing capability.

Leveraging semantic caching and tiered routing

Optimizing your AI architecture means looking beyond the base token price. By implementing semantic caching at the edge, utilizing provider-level prompt caching for large context windows, and shifting asynchronous workloads to Batch APIs, organizations in Australia and the US routinely cut their monthly LLM spend by 40-60%. Use the toggles above to simulate these architectural savings.

Embed-ready

Need this live Overall data on your website?

Join 500+ agencies in the US and Australia using LeadsCalc to capture high-intent leads. Embed this interactive Overall leaderboard on your site in about a minute—Canadian teams use the same flows for CAD-priced proposals and compliance-friendly landing pages.

Customize & Embed this ToolWhite-label · No code required
United StatesCanadaAustralia
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Your visitors compare Overall models without leaving your domain.

Support & clarity

Frequently Asked Questions

Focused on teams in the United States, Canada, and Australia.

Use it to shortlist 3–5 models, then drill into category tabs that match your workload (coding, reasoning, cost). Agencies commonly share this view with clients to align on model choices before implementation.