AI Model Capability Comparison

Multimodal

Only models released within the past year are shown. Only benchmarks covering at least 3 of these models are shown. Unknown release dates are excluded; historical data is retained.

SWE-bench MultimodalMultimodal software engineering benchmark

— means no published score for this candidate in this source, not zero.8/11 recent-year models have scores

No.ModelCost / TestCost per testInput costInput price per million tokensOutput costOutput price per million tokensDurationReported test durationInput / Output TokensReported input / output token usage
1AnthropicClaude Opus 5.5Claude Opus 5.570.21$4.92$4$2018.53 min3.18B / 38.08M
2AnthropicClaude Fable 5.1Claude Fable 5.161.25$5.46$10$5015.2 min2.21B / 27.94M
3AnthropicClaude Sonnet 5.5Claude Sonnet 5.558.33$4.53$2$1024.22 min6.21B / 67.48M
4Google DeepMindGemini 4 ArgonGemini 4 Argon56.04$11.4$4$2033.63 min6.54B / 56.31M
5AnthropicClaude Haiku 5.5Claude Haiku 5.543.96$0.7$0.1$0.516.27 min4.64B / 62.24M
6OpenAIGPT-6.1 SolGPT-6.1 Sol43.54$0.35$2$106.93 min242.14M / 8.75M
7OpenAIGPT-6 AstraGPT-6 Astra43.33$1.81$10$507.05 min222.91M / 7.78M
8OpenAIGPT-6 LunaGPT-6 Luna37.5$0.03$0.1$0.55.27 min524.11M / 13.09M

Vals.ai benchmarks

Source: Vals.ai ↗ · Updated 2026-10-19

SWE-bench Multimodal · Updated 2026-10-16

PandaNpc Updated Oct 21, 2026, 06:01 UTC

Source: Epoch AI, CC BY 4.0 · Vals.ai · Artificial Analysis (artificialanalysis.ai)

Column guide

No.
Display order only. Sorting changes this number; it is not a published capability rank.
Model
The evaluated model name and its provider icon. A dash in a score column means no published score is available here, not a zero.
Score
Tests software engineering tasks that require visual information as well as code, such as interpreting screenshots of an interface. Evaluation methodology ↗
Cost / Test
Cost per test · USD
Input cost
Input price per million tokens · USD / 1M tokens
Output cost
Output price per million tokens · USD / 1M tokens
Duration
Reported test duration · s / min
Input / Output Tokens
Reported input / output token usage · tokens
Vals.ai
Costs and times are reported by Vals for this benchmark, not universal model prices or latency. CUA-bench estimated API cost covers evaluation usage and is a lower-bound estimate, not cost per task; time per action is an average, not a median. An asterisk marks launch-day prompt-cache behavior that increased cache-write costs. Missing values are unpublished, not zero.