ELYZA Japanese Llama 2 7B vs GPT-4 Turbo
ELYZA Japanese Llama 2 7B (2023) and GPT-4 Turbo (2024) are compact production models from ELYZA and OpenAI. ELYZA Japanese Llama 2 7B ships a not-yet-sourced context window, while GPT-4 Turbo ships a 128k-token context window. On pricing, ELYZA Japanese Llama 2 7B costs $0.20/1M input tokens versus $5/1M for the alternative. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads.
ELYZA Japanese Llama 2 7B is ~2400% cheaper at $0.20/1M; pay for GPT-4 Turbo only for coding workflow support.
Decision scorecard
Local evidence first| Signal | ELYZA Japanese Llama 2 7B | GPT-4 Turbo |
|---|---|---|
| Best for | provider-routed production | multimodal apps, tool-calling agents, and provider-routed production |
| Decision fit | General | Coding, RAG, and Agents |
| Context window | — | 128k |
| Cheapest output | $0.20/1M tokens | $15/1M tokens |
| Provider routes | 2 tracked | 6 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- ELYZA Japanese Llama 2 7B has the lower cheapest tracked output price at $0.20/1M tokens.
- GPT-4 Turbo has the larger context window for long prompts, retrieval packs, or transcript analysis.
- GPT-4 Turbo has broader tracked provider coverage for fallback and procurement flexibility.
- GPT-4 Turbo uniquely exposes Vision, Multimodal, and Function calling in local model data.
- Local decision data tags GPT-4 Turbo for Coding, RAG, and Agents.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output route or tier on this page.
ELYZA Japanese Llama 2 7B
$210
Cheapest tracked route/tier: Fireworks AI
GPT-4 Turbo
$7,750
Cheapest tracked route/tier: Replicate API
Estimated monthly gap: $7,540. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.
Switch friction
- No overlapping tracked provider route is sourced for ELYZA Japanese Llama 2 7B and GPT-4 Turbo; plan for SDK, billing, or endpoint changes.
- GPT-4 Turbo is $14.80/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- GPT-4 Turbo adds Vision, Multimodal, and Function calling in local capability data.
- No overlapping tracked provider route is sourced for GPT-4 Turbo and ELYZA Japanese Llama 2 7B; plan for SDK, billing, or endpoint changes.
- ELYZA Japanese Llama 2 7B is $14.80/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for Vision, Multimodal, and Function calling before moving production traffic.
Specs
| Specification | ||
|---|---|---|
| Released | 2023-08-02 | 2024-04-09 |
| Context window | — | 128k |
| Parameters | 7B | 1.76T (8x222B MoE)* |
| Architecture | decoder only | mixture of experts |
| License | Llama 2 Community | Proprietary |
| Openness | Open weights | Proprietary |
| Commercial use | Commercial use with conditions | Commercial use with conditions |
| Knowledge cutoff | - | 2023-12 |
Pricing and availability
| Pricing attribute | ELYZA Japanese Llama 2 7B | GPT-4 Turbo |
|---|---|---|
| Input price | $0.20/1M tokens | $5/1M tokens |
| Output price | $0.20/1M tokens | $15/1M tokens |
| Providers |
Capabilities
| Capability | ELYZA Japanese Llama 2 7B | GPT-4 Turbo |
|---|---|---|
| Vision | No | Yes |
| Multimodal | No | Yes |
| Reasoning | No | No |
| Function calling | No | Yes |
| Tool use | No | Yes |
| Structured outputs | No | Yes |
| Code execution | No | Yes |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
No shared benchmark rows are currently sourced for this pair.
Deep dive
The capability footprint differs most on vision: GPT-4 Turbo, multimodal input: GPT-4 Turbo, function calling: GPT-4 Turbo, tool use: GPT-4 Turbo, structured outputs: GPT-4 Turbo, and code execution: GPT-4 Turbo. 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, ELYZA Japanese Llama 2 7B lists $0.20/1M input and $0.20/1M output tokens on the cheapest tracked provider, while GPT-4 Turbo lists $5/1M input and $15/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts ELYZA Japanese Llama 2 7B lower by about $7.80 per million blended tokens. Availability is 2 providers versus 6, so concentration risk also matters.
Choose ELYZA Japanese Llama 2 7B when provider fit and lower input-token cost are central to the workload. Choose GPT-4 Turbo when coding workflow support 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 is cheaper, ELYZA Japanese Llama 2 7B or GPT-4 Turbo?
ELYZA Japanese Llama 2 7B is cheaper on tracked token pricing. ELYZA Japanese Llama 2 7B costs $0.20/1M input and $0.20/1M output tokens. GPT-4 Turbo costs $5/1M input and $15/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is ELYZA Japanese Llama 2 7B or GPT-4 Turbo open source?
ELYZA Japanese Llama 2 7B is listed under Llama 2 Community. GPT-4 Turbo is listed under Proprietary. 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 vision, ELYZA Japanese Llama 2 7B or GPT-4 Turbo?
GPT-4 Turbo has the clearer documented vision signal in this comparison. If vision is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Which is better for multimodal input, ELYZA Japanese Llama 2 7B or GPT-4 Turbo?
GPT-4 Turbo has the clearer documented multimodal input signal in this comparison. If multimodal input is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Which is better for function calling, ELYZA Japanese Llama 2 7B or GPT-4 Turbo?
GPT-4 Turbo has the clearer documented function calling signal in this comparison. If function calling is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Where can I run ELYZA Japanese Llama 2 7B and GPT-4 Turbo?
ELYZA Japanese Llama 2 7B is available on Fireworks AI and IBM watsonx. GPT-4 Turbo is available on OpenAI API, Azure OpenAI, Salesforce Einstein Generative AI, OpenRouter, and Replicate API. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
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Last reviewed: 2026-05-22. Data sourced from public model cards and provider documentation.