Command A Plus 05 2026 BF16 vs Llama 3.1 70B Instruct
At a Glance
| Compare | ||
|---|---|---|
| Pricing and Limits | ||
| Input priceFrom · USD / 1M tokens | Not reported | $0.40Openrouter ↗ · Sep 22, 2026 |
| Output priceFrom · USD / 1M tokens | Not reported | $0.40Openrouter ↗ · Sep 22, 2026 |
| Context windowMaximum documented tokens | 200K | 131K |
| Model facts checked | Aug 28, 2026View model evidence → | Aug 28, 2026View model evidence → |
Token prices are the lowest available sourced USD rates; input and output may use different providers. Cost ranking estimates output spend on LiveBench, not a full request bill. Ranking methodology →
Available Benchmarks
Side-by-Side Facts
| Field | command-a-plus-05-2026-bf16 | Llama-3.1-70B-Instruct |
|---|---|---|
| Developer | Cohere | Meta |
| Family | Command A Plus 05 | Llama 3 1 70b Instruct |
| Model | command-a-plus-05-2026-bf16 | Llama-3.1-70B-Instruct |
| Version | command-a-plus-05-2026-bf16 | Llama-3.1-70B-Instruct |
| Lifecycle | active | active |
| Released | Unknown | 2024-07-23 |
| Knowledge cutoff | Unknown | Unknown |
| Input modalities | Text, Image | Text |
| Output modalities | Text | Text |
| Context window | 200K | 131K |
| Total parameters | 218.8B | 70.6B |
| Active parameters | 25B | Unknown |
| License | apache-2.0 | llama3.1 |
| Open weights | Yes | Yes |
| API available | Unknown | Yes |
| Self-hostable | Yes | Yes |
| Provider access | Unknown | Openrouter (Standard) |
| Capabilities | chat, generation, tools | chat, generation, tools |
Command A Plus 05 2026 BF16 Capabilities
Llama 3.1 70B Instruct Capabilities
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Primary Evidence
Sources and Freshness
Questions
Command A Plus 05 2026 BF16 vs Llama 3.1 70B Instruct FAQs
Is Command A Plus 05 2026 BF16 or Llama 3.1 70B Instruct better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Command A Plus 05 2026 BF16 and Llama 3.1 70B Instruct, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, Command A Plus 05 2026 BF16 or Llama 3.1 70B Instruct?+
Only Llama 3.1 70B Instruct has a directly sourced input price: $0.40 per million tokens. Only Llama 3.1 70B Instruct has a directly sourced output price: $0.40 per million tokens.
Which has a larger context window, Command A Plus 05 2026 BF16 or Llama 3.1 70B Instruct?+
Command A Plus 05 2026 BF16 has the larger sourced context window. Command A Plus 05 2026 BF16 supports 200K and Llama 3.1 70B Instruct supports 131K.
Which performs better in benchmarks, Command A Plus 05 2026 BF16 or Llama 3.1 70B Instruct?+
There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.
Can Command A Plus 05 2026 BF16 or Llama 3.1 70B Instruct be self-hosted?+
Both models have the same recorded self-hosting status: supported. Command A Plus 05 2026 BF16 is open weight; Llama 3.1 70B Instruct is open weight.
Can Command A Plus 05 2026 BF16 and Llama 3.1 70B Instruct understand images?+
Command A Plus 05 2026 BF16 is documented with image input; Llama 3.1 70B Instruct is not documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, Command A Plus 05 2026 BF16 or Llama 3.1 70B Instruct?+
Neither has a larger sourced maximum output. Command A Plus 05 2026 BF16 is 66K and Llama 3.1 70B Instruct is —.
Do Command A Plus 05 2026 BF16 and Llama 3.1 70B Instruct support reasoning and tool use?+
Command A Plus 05 2026 BF16: tool calling and image input. Llama 3.1 70B Instruct: tool calling. Feature support does not establish relative quality.
Which is available from more inference providers, Command A Plus 05 2026 BF16 or Llama 3.1 70B Instruct?+
Command A Plus 05 2026 BF16 has 0 sourced provider routes; Llama 3.1 70B Instruct has 1, so Llama 3.1 70B Instruct has broader tracked availability.
Which offers better value, Command A Plus 05 2026 BF16 or Llama 3.1 70B Instruct?+
There is no universal value winner. Compare the input and output prices above with the matched benchmark result for your workload: cheaper tokens can be offset by different quality, token usage, latency, or provider availability.