Command R vs Llama-3.2-11B-Vision-Instruct vs Qwen Flash
Qwen Flash comes out ahead, 68 to 58 and 51 on our weighted score, and it is the cheaper option too.
CohereCommand R
51/100- ECI—
- Price$0.15 / $0.60
- Context128K
MetaLlama-3.2-11B-Vision-Instruct
58/100- ECI—
- Price$0.197 / $0.51
- Context128K
- Our pick
Alibaba (Qwen)Qwen Flash
68/100- ECI—
- Price$0.05 / $0.40
- Context1M
Qwen Flash is our pick
Qwen Flash is the better all-round choice, scoring 68/100 against Llama-3.2-11B-Vision-Instruct (58) and Command R (51). It leads on price and context window. Llama-3.2-11B-Vision-Instruct wins on inputs & features. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
- CapabilityNot enough dataNo independent benchmark covers every model here yet
- Lowest priceQwen FlashQwen Flash $0.138 · Command R $0.263 · Llama-3.2-11B-Vision-Instruct $0.275 per 1M tokens (3:1 blend)
- Longest contextQwen FlashQwen Flash 1,000,000 · Command R 128,000 · Llama-3.2-11B-Vision-Instruct 128,000 tokens
- Widest inputsLlama-3.2-11B-Vision-InstructCommand R: Text · Llama-3.2-11B-Vision-Instruct: Text, Images · Qwen Flash: Text
- Self-hostingCommand R and Llama-3.2-11B-Vision-InstructPublishes downloadable weights
| Measure | Weight | Command R | Llama-3.2-11B-Vision-Instruct | Qwen Flash |
|---|---|---|---|---|
| Price | 50% | 77 | 76 | 91 |
| Inputs & features | 30% | 25 | 50 | 35 |
| Context window | 20% | 24 | 24 | 60 |
| Overall | 100% | 51/100 | 58/100 | 68/100 |
Left out because at least one model lacks the data: capability. The remaining weights were rescaled.
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Command RCohere | Llama-3.2-11B-Vision-InstructMeta | Qwen FlashAlibaba (Qwen) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.15 | $0.197 | $0.05 (best) |
| Output | $0.60 | $0.51 | $0.40 (best) |
| Cached input | — | — | — |
| Blended (3:1) | $0.263 | $0.275 | $0.138 (best) |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Cohere API | Median of 2 providers | Official Alibaba API |
| Limits | |||
| Context window | 128,000 tokens | 128,000 tokens | 1,000,000 tokens (best) |
| Max output | 4,000 tokens | 4,096 tokens | 32,768 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | Yes | No |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | No | No | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | Open | Open | Proprietary |
| API model ID | command-r-08-2024 | — | qwen-flash |
| API providers | 5 | 2 | 6 (best) |
| Released | Aug 30, 2024 | Sep 25, 2024 | Jul 28, 2025 |
| Knowledge cutoff | Jun 1, 2024 | Dec 2023 | Apr 2024 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Command R$2.70
- Llama-3.2-11B-Vision-Instruct$2.99
- Qwen Flash$1.30
Which should you choose?
Which is better: Command R, Llama-3.2-11B-Vision-Instruct or Qwen Flash?
Qwen Flash is the better all-round choice, scoring 68/100 against Llama-3.2-11B-Vision-Instruct (58) and Command R (51). It leads on price and context window. Llama-3.2-11B-Vision-Instruct wins on inputs & features. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
Which is cheaper, Command R, Llama-3.2-11B-Vision-Instruct or Qwen Flash?
Qwen Flash is cheaper at $0.05 input / $0.40 output per million tokens (official Alibaba API price). Command R costs $0.15 input / $0.60 output per million tokens (official Cohere API price); Llama-3.2-11B-Vision-Instruct costs $0.197 input / $0.51 output per million tokens (median across 2 API providers). At a typical mix of three input tokens to one output token, that is $0.138 per million tokens for Qwen Flash versus $0.263 for Command R (1.9× as much) and $0.275 for Llama-3.2-11B-Vision-Instruct (2× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Command R has not been scored yet, Llama-3.2-11B-Vision-Instruct has not been scored yet and Qwen Flash has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Command R, Llama-3.2-11B-Vision-Instruct and Qwen Flash yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. All three support tool calling for agent workflows.
Which has the bigger context window?
Qwen Flash has the largest context window at 1,000,000 tokens, against 128,000 for Command R and 128,000 for Llama-3.2-11B-Vision-Instruct. Maximum output per response: Command R up to 4,000, Llama-3.2-11B-Vision-Instruct up to 4,096, Qwen Flash up to 32,768 tokens.
Which can read images, PDFs, audio or video?
Command R accepts text; Llama-3.2-11B-Vision-Instruct accepts text and images; Qwen Flash accepts text. Llama-3.2-11B-Vision-Instruct handles the widest range of inputs.
Are any of these open source?
Command R and Llama-3.2-11B-Vision-Instruct publishes its weights and can be self-hosted; Qwen Flash is proprietary.
Which is newer?
Qwen Flash is the newest, released Jul 28, 2025. Llama-3.2-11B-Vision-Instruct came out Sep 25, 2024; Command R came out Aug 30, 2024. Knowledge cutoff: Command R Jun 1, 2024, Llama-3.2-11B-Vision-Instruct Dec 2023, Qwen Flash Apr 2024.
How do you decide the winner?
Each model gets a 0–100 score on capability (50%, independent benchmark results); price (25%, blended price per million tokens (3 input : 1 output), log scale); inputs & features (15%, image, PDF, audio and video input, tool calling, structured output and reasoning); context window (10%, maximum tokens per request, log scale). Dimensions missing for any model are dropped and the remaining weights rescaled, so every model is judged on the same evidence. Specs and prices come from public model listings and the labs’ own API pages; capability scores come from independent benchmark runs. Data updated Oct 4, 2026.
