Compare AI models
| Specifications | ||
ParametersThe learned values that shape how a model responds. B means billion and T means trillion. For mixture-of-experts models, the total count is larger than the number active for each token. Parameter count alone does not measure quality. | 2B/7B | 816B |
Context windowHow much information the model can work with in one request, measured in tokens — pieces of words or other data. This includes your question, attachments, conversation and reply. Limits can vary by model variant and provider. | 8k | 1M |
| API pricingUSD per 1M tokens · lower wins | ||
Cheapest inputLowest input rate across every provider on OpenRouter, the lab included. The cheapest endpoint may run a quantised build or a shorter context — see "Available from" on the model page. | — | $1.25BaseTen |
Cheapest outputLowest output rate across every provider on OpenRouter, the lab included. May come from a different provider than the cheapest input. | — | $4.25BaseTen |
| — | $463Modal | |
| These models have no shared benchmark scores. | ||
DeepSWE 1.1Agentic coding — Artificial Analysis' independent test of deep, agentic software-engineering work — the AI has to plan and carry out substantial coding tasks end to end. (Version 1.1 of the test.) Higher is better. | — | 60% |
Terminal-Bench 2.1Agentic terminal coding — Can the AI work in a command-line terminal — running commands and finishing technical setup tasks the way a developer would? Higher is better. | — | 76.4% |
MCP AtlasMulti-step tool use — Can the AI chain together many tools and steps to complete one bigger task, rather than doing just a single thing? Higher is better. | — | 89.2% |
JobBenchProfessional tool use — Tests the AI on professional workplace tasks that require using real work tools — the kind of multi-step jobs an office worker handles. Higher is better. | — | 61.8% |
GDPval-AA v2Knowledge work — economically valuable knowledge work (v2, re-based Elo) | — | 1401 |
| Overview | ||
| Company | Meta | |
| Release date | Feb 21 2024 | Oct 15 2026 |
| Access | Open Weight | Open Weight |
| Model details | View model | View model |
Other comparisons
Gemma 1vsClaude Haiku 5.5Muse Spark OpenvsClaude Haiku 5.5Gemma 1vsGPT-6.1 SolMuse Spark OpenvsGPT-6.1 SolGemma 1vsGrok 4.7Muse Spark OpenvsGrok 4.7Gemma 1vsDeepSeek-V4.1-Flash-1017Muse Spark OpenvsDeepSeek-V4.1-Flash-1017Gemma 1vsMistral Large 4Muse Spark OpenvsMistral Large 4Gemma 1vsKimi K3Muse Spark OpenvsKimi K3Frequently asked questions
Gemma 1 and Muse Spark Open don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Gemma 1 shipped 967 days before Muse Spark Open, so benchmark comparisons should account for the intervening progress.
Gemma 1 has 2B/7B parameters, while Muse Spark Open has 816B. Context windows are 8k (Gemma 1) vs 1M (Muse Spark Open).
Direct benchmark comparisons are unavailable — Gemma 1 and Muse Spark Open don't publish scores on any of the same benchmarks.