Llama 2 13B Chat vs Mixtral 8x7B
Llama 2 13B Chat (2023) and Mixtral 8x7B (2023) are compact production models from AI at Meta and MistralAI. Llama 2 13B Chat ships a 4k-token context window, while Mixtral 8x7B ships a 32k-token context window. On Google-Proof Q&A, Mixtral 8x7B leads by 13 pts. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads.
Llama 2 13B Chat is ~50% cheaper at $0.10/1M; pay for Mixtral 8x7B only for long-context analysis.
Decision scorecard
Local evidence first| Signal | Llama 2 13B Chat | Mixtral 8x7B |
|---|---|---|
| Best for | provider-routed production | provider-routed production |
| Decision fit | Coding, Classification, and JSON / Tool use | Coding and Classification |
| Context window | 4k | 32k |
| Cheapest output | $0.50/1M tokens | $0.45/1M tokens |
| Provider routes | 11 tracked | 18 tracked |
| Shared benchmarks | 4 rows | Google-Proof Q&A leader |
Decision tradeoffs
- Llama 2 13B Chat uniquely exposes Structured outputs in local model data.
- Local decision data tags Llama 2 13B Chat for Coding, Classification, and JSON / Tool use.
- Mixtral 8x7B holds a shared-benchmark lead on Google-Proof Q&A, ahead by 13 points.
- Mixtral 8x7B has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Mixtral 8x7B has the lower cheapest tracked output price at $0.45/1M tokens.
- Mixtral 8x7B has broader tracked provider coverage for fallback and procurement flexibility.
- Local decision data tags Mixtral 8x7B for Coding and Classification.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output route or tier on this page.
Llama 2 13B Chat
$205
Cheapest tracked route/tier: Replicate API
Mixtral 8x7B
$233
Cheapest tracked route/tier: Mistral AI Studio
Estimated monthly gap: $27.50. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on Databricks Foundation Model Serving, GCP Vertex AI, and AWS Bedrock; start route-level A/B tests there.
- Mixtral 8x7B is $0.05/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for Structured outputs before moving production traffic.
- Provider overlap exists on Alibaba Cloud PAI-EAS, AWS Bedrock, and Microsoft Foundry; start route-level A/B tests there.
- Llama 2 13B Chat is $0.05/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Llama 2 13B Chat adds Structured outputs in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2023-07-18 | 2023-12-11 |
| Context window | 4k | 32k |
| Parameters | 13B | 8x7B |
| Architecture | decoder only | mixture of experts |
| License | Llama 2 Community | Apache 2.0(OSI) |
| Openness | Open weights | Open source |
| Commercial use | Commercial use with conditions | Commercial use allowed |
| Knowledge cutoff | 2022-09 | 2023-12 |
Pricing and availability
| Pricing attribute | Llama 2 13B Chat | Mixtral 8x7B |
|---|---|---|
| Input price | $0.10/1M tokens | $0.15/1M tokens |
| Output price | $0.50/1M tokens | $0.45/1M tokens |
| Providers |
Capabilities
| Capability | Llama 2 13B Chat | Mixtral 8x7B |
|---|---|---|
| Vision | No | No |
| Multimodal | No | No |
| Reasoning | No | No |
| Function calling | No | No |
| Tool use | No | No |
| Structured outputs | Yes | No |
| Code execution | No | No |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
| Benchmark | Llama 2 13B Chat | Mixtral 8x7B |
|---|---|---|
| Google-Proof Q&A | 41.8 | 54.8 |
| HumanEval | 59.3 | 80.5 |
| Massive Multitask Language Understanding | 71.2 | 80.2 |
| HellaSwag | 88.5 | 90.9 |
Deep dive
On shared benchmark coverage, Google-Proof Q&A has Llama 2 13B Chat at 41.8 and Mixtral 8x7B at 54.8, with Mixtral 8x7B ahead by 13 points; HumanEval has Llama 2 13B Chat at 59.3 and Mixtral 8x7B at 80.5, with Mixtral 8x7B ahead by 21.2 points; Massive Multitask Language Understanding has Llama 2 13B Chat at 71.2 and Mixtral 8x7B at 80.2, with Mixtral 8x7B ahead by 9 points. The largest visible gap is 21.2 points on HumanEval, which matters most when that benchmark mirrors your workload. Treat isolated benchmark wins as directional, because provider routing, prompt style, and tool access can move real application results.
The capability footprint differs most on structured outputs: Llama 2 13B Chat. Both models share the core language-model surface, so the practical split is not just feature count. Use those differences to decide whether the page is about raw model quality, agentic coding support, multimodal ingestion, or predictable structured API behavior.
For cost, Llama 2 13B Chat lists $0.10/1M input and $0.50/1M output tokens on the cheapest tracked provider, while Mixtral 8x7B lists $0.15/1M input and $0.45/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Llama 2 13B Chat lower by about $0.02 per million blended tokens. Availability is 11 providers versus 18, so concentration risk also matters.
Choose Llama 2 13B Chat when provider fit and lower input-token cost are central to the workload. Choose Mixtral 8x7B when long-context analysis, larger context windows, and broader provider choice are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship.
FAQ
Which has a larger context window, Llama 2 13B Chat or Mixtral 8x7B?
Mixtral 8x7B supports 32k tokens, while Llama 2 13B Chat supports 4k tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.
Which is cheaper, Llama 2 13B Chat or Mixtral 8x7B?
Llama 2 13B Chat is cheaper on tracked token pricing. Llama 2 13B Chat costs $0.10/1M input and $0.50/1M output tokens. Mixtral 8x7B costs $0.15/1M input and $0.45/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Llama 2 13B Chat or Mixtral 8x7B open source?
Llama 2 13B Chat is listed under Llama 2 Community. Mixtral 8x7B is listed under Apache 2.0. License labels affect whether you can self-host, redistribute weights, or rely only on hosted APIs, so confirm the upstream license before deployment.
Which is better for structured outputs, Llama 2 13B Chat or Mixtral 8x7B?
Llama 2 13B Chat has the clearer documented structured outputs signal in this comparison. If structured outputs is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Where can I run Llama 2 13B Chat and Mixtral 8x7B?
Llama 2 13B Chat is available on Alibaba Cloud PAI-EAS, AWS Bedrock, Microsoft Foundry, GCP Vertex AI, and DeepInfra. Mixtral 8x7B is available on Databricks Foundation Model Serving, NVIDIA NIM, GCP Vertex AI, AWS Bedrock, and OctoAI API (Deprecated). Provider coverage can affect latency, region availability, compliance posture, and fallback options.
When should I pick Llama 2 13B Chat over Mixtral 8x7B?
Llama 2 13B Chat is ~50% cheaper at $0.10/1M; pay for Mixtral 8x7B only for long-context analysis. If your workload also depends on provider fit, start with Llama 2 13B Chat; if it depends on long-context analysis, run the same evaluation with Mixtral 8x7B.
Continue comparing
Last reviewed: 2026-05-16. Data sourced from public model cards and provider documentation.