Grafana Alternatives for LLMs in 2026: 7 Platforms Compared

The best Grafana alternatives for LLM observability in 2026 are Future AGI, Datadog Agent Observability, Langfuse, Arize Phoenix, Helicone, New Relic and Honeycomb. Grafana is still excellent for infrastructure time series, and Grafana Cloud now ships Agent Observability, but self-managed Grafana leaves span-attached evals, prompt versions and dataset replay to you. This guide compares the seven on LLM depth, license and pricing.

Best Grafana alternative for LLMs per use case

If you only read one row: pick Future AGI when LLM observability is the dominant workload. Pick Datadog when the constraint is one tool for everything. Pick Honeycomb when query power matters more than integrated breadth.

Who Grafana is and where it falls short for LLMs

Grafana is the open-source dashboard platform at the center of the Grafana Labs stack, which also includes Loki for logs, Tempo for distributed traces, Mimir for metrics, and Pyroscope for profiling. The combination is strong for infrastructure observability: latency dashboards, error budgets, cost panels, alerting via Alertmanager.

The visualization surface is excellent: panel types, query languages (PromQL, LogQL, TraceQL), templating, and alerting are all mature. The OSS license (AGPLv3 core) keeps the platform inspectable. Grafana Cloud and Grafana Enterprise add hosted and on-prem deployment with team workflows.

Teams start looking elsewhere when they reach the LLM layer. In self-managed Grafana, span-attached eval scores are not first-class: you can join traces and eval scores in a custom panel, but prompt versions, dataset replay and CI gating stay outside the stack. Grafana Cloud closed part of that gap with Agent Observability, covered below, yet Grafana lists no self-managed release of it.

License posture and LLM surface coverage across the 2026 Grafana alternatives

Future AGI pairs an Apache-2.0 core with LLM-specific dashboards built on OpenTelemetry spans: latency, token usage, errors and eval scores in one view.

What Grafana LLM observability covers now

Grafana Cloud has its own answer for LLM workloads. Agent Observability became generally available in Grafana Cloud on July 30, 2026. It adds agent sessions as a fifth telemetry signal next to metrics, logs, traces and profiles, shows spend per agent, model and session, and scores response quality continuously with alerts when pass rates drop.

On October 20, 2026, Grafana Labs announced OpenTelemetry support for Agent Observability. Agents that already emit OpenTelemetry GenAI spans can send them through Grafana Alloy or an OpenTelemetry Collector without the SDK. Grafana’s docs also list online evaluations and guards for production traffic, plus offline experiments that compare models, prompts and agent versions.

Deployment is where it stops: Grafana lists no self-managed release of Agent Observability, so teams on self-hosted Grafana still build LLM panels by hand. Grafana Cloud’s free tier includes 30k generations a month, and Pro starts at $1.50 per 1k generations beyond the 30k included in a $19 monthly platform fee. For agent-specific tools beyond this list, see Best AI Agent Observability Tools.

Grafana Tempo alternatives for LLM traces

Grafana Tempo is the trace store in the Grafana stack. If you replace it for LLM spans, each of these accepts OpenTelemetry traces directly:

• Future AGI: OTLP ingest for traces, with spans stored in ClickHouse.
• Langfuse: OTLP over HTTP at /api/public/otel; gRPC is not supported.
• Arize Phoenix: accepts traces over OTLP.
• Datadog Agent Observability: accepts spans that follow the OpenTelemetry 1.37+ GenAI conventions.

The 7 Grafana alternatives for LLMs compared

1. Future AGI: Best for unified LLM dashboards

Apache-2.0 core. Self-hostable. Hosted cloud option.

Future AGI ships span trees plus LLM-specific dashboards out of the box: latency, token usage, error counts and eval scores, grouped by model, user or any span attribute. The pitch is one platform across simulate, evaluate, observe, gate, optimize, and route. For teams that want LLM observability without rebuilding panels in Grafana, Future AGI is the lowest-friction alternative.

Architecture: Apache-2.0 core and self-hostable. ClickHouse handles high-volume trace storage. The UI ships dashboards for each LLM-specific surface. OTel ingestion across Python, TypeScript, Java, and C# means the platform works across multi-language services.

Pricing: Free + pay-as-you-go base. Compliance (SOC 2 Type II, HIPAA BAA), SSO (OAuth, SAML + SCIM), and enterprise SLAs add on as you scale.

Best for: Teams whose dominant workload is LLM applications and who want LLM-specific dashboards without building them in Grafana.

2. Datadog Agent Observability: Best when Datadog is already the standard

Closed platform. SaaS with regional residency. APM-integrated.

Datadog is the right alternative when the team already runs Datadog for APM, infrastructure, and logs and wants LLM spans next to existing telemetry rather than in a separate tool. Datadog correlates LLM trace spans with database queries, downstream service latency, and infrastructure events. Datadog now lists the product as Agent Observability in its docs and pricing.

Pricing: Datadog lists APM at $31/host/mo billed annually. Agent Observability has a free tier of up to 40K LLM spans a month, and paid use starts at $160/mo billed annually for the first 100K LLM spans with 15-day retention.

OSS status: Closed platform.

Best for: Enterprise teams where Datadog is the system of record and the goal is one tool for APM, logs, RUM, security, and LLM observability.

Skip if: Skip Datadog if open-source control matters or if cost predictability is the constraint. See Braintrust vs Datadog LLM Observability for the head-to-head.

3. Langfuse: Best for self-hosted LLM observability

Open source core. Self-hostable. Hosted cloud option.

Langfuse is the strongest OSS-first alternative for self-hosted LLM observability with prompts and datasets. It fits teams where “no black-box SaaS for traces” is a hard requirement. It pairs with Grafana for infrastructure dashboards. ClickHouse acquired Langfuse on January 16, 2026; the core stays MIT and Langfuse Cloud runs as a standalone service.

Pricing: Langfuse Cloud starts free on Hobby with 50,000 units/mo. Core $29/mo with 100,000 units. Pro $199/mo with 3 years data access. Enterprise $2,499/mo.

OSS status: MIT core, enterprise directories handled separately.

Best for: Platform teams that operate the data plane and want trace data in their own infrastructure, paired with Grafana for infrastructure dashboards.

Skip if: Skip Langfuse if your gap is simulated users, voice evaluation, prompt optimization algorithms, or runtime guardrails. See Langfuse Alternatives.

4. Arize Phoenix: Best for OpenTelemetry-native ingestion

Source available. Self-hostable. Phoenix Cloud and Arize AX paths exist.

Pick Phoenix when open instrumentation standards drive the choice. Phoenix accepts traces over OTLP and auto-instruments LlamaIndex, LangChain, DSPy, Mastra, Vercel AI SDK, OpenAI Agents SDK, Bedrock, Anthropic, Python, TypeScript, and Java. Phoenix stores traces in SQLite by default or PostgreSQL in production.

Pricing: Phoenix is free for self-hosting. AX Free is 25K spans/mo, 1 GB ingestion, 15 days retention. AX Pro is $50/mo with 50K spans, 30 days retention.

OSS status: Elastic License 2.0. Source available, with restrictions on offering as a managed service.

Best for: Engineers who care about open instrumentation standards and want a clean local Phoenix workbench for development.

Skip if: ELv2 license matters if your legal team uses OSI definitions strictly.

5. Helicone: Best for gateway-first observability

Open source. Self-hostable. Hosted cloud option.

Pick Helicone when the fastest path to traces is changing the base URL. The gateway captures every request, then surfaces sessions, user metrics, cost tracking, prompts, and eval scores. It beats rebuilding LLM dashboards in Grafana.

Pricing: Helicone Hobby is free with 10,000 requests, 1 GB storage, 1 seat. Pro is $79/mo with unlimited seats, alerts, reports, HQL. Team is $799/mo.

OSS status: Apache 2.0.

Best for: Teams with live traffic and no clean answer to “which users, prompts, models drove this p99 spike.”

Skip if: Mintlify acquired Helicone on March 3, 2026 and put it in maintenance mode. As of October 2026, Helicone’s site says it is no longer part of Mintlify, with details to come, so confirm its support status before you commit.

6. New Relic: Best when New Relic is already the standard

Closed platform. SaaS. APM-integrated.

New Relic is the right alternative for teams already standardized on New Relic for APM, infrastructure, and logs. AI Monitoring adds LLM-specific cost and latency tracking, prompt and response capture, and integration into the broader APM surface.

Pricing: New Relic’s free tier includes 100 GB/mo of data ingest and one full platform user. Standard costs $10 for the first full platform user and $99 for each additional one, with a limit of five full platform users; Pro is $349 per user on annual terms, and Enterprise is quote-based.

OSS status: Closed platform.

Best for: Enterprise teams where New Relic is the system of record and the goal is one tool for APM, logs, infra, and LLM observability.

Skip if: Skip New Relic if open-source control matters or if the LLM surface needs deeper eval, simulation, or guardrails than the AI Monitoring extension provides.

7. Honeycomb: Best for high-cardinality query and tracing

Closed platform. SaaS. OTel-native.

Honeycomb is the right alternative when query power matters more than integrated breadth. The pitch is high-cardinality, schema-less query over traces: “show me all spans where the user_id is X, the model is Y, the latency is above 5 seconds, and the eval score is below 0.8.” Agent Timeline, generally available since June 18, 2026, shows LLM behavior and multi-agent workflows in one unified view.

Pricing: Honeycomb Free covers up to 20M events/mo. Pro starts at $150/mo for 50M events, scales up to 750M events/mo and adds SSO. Enterprise plans are custom and start at 10 billion events per year.

OSS status: Closed platform.

Best for: SREs and platform engineers who already use Honeycomb for general observability and want LLM trace query as a complementary surface.

Skip if: Skip Honeycomb if you need a first-party LLM eval engine, prompt management, or simulation. Its documented eval pattern brings scores in from a separate framework such as Braintrust, as spans on the trace.

Langfuse vs Grafana

Langfuse and Grafana answer different questions. Langfuse is an open-source LLM engineering platform that shows what a model saw, returned and cost on each request, with prompts, datasets and evals attached. Grafana shows whether the system around it is healthy, through metrics, logs, traces and alerting across the stack.

Grafana Cloud’s Agent Observability now overlaps on sessions, cost and quality scores, but Langfuse self-hosts with an MIT core, and Grafana lists no self-managed release of its agent features. For a Langfuse Grafana integration, use the Langfuse Metrics API, which Langfuse documents for custom dashboards and which aggregates cost, token usage, volume, latency and score data.

Decision framework: pick by constraint

• OSS is non-negotiable: Future AGI, Langfuse, Helicone. Add Phoenix if “source available” is acceptable.
• Already on Datadog for everything: Datadog Agent Observability.
• Already on New Relic for APM: New Relic AI Monitoring.
• Query power matters most: Honeycomb.
• Grafana alternatives you can self-host: Future AGI, Langfuse, Phoenix, Helicone.
• Gateway-first: Helicone.
• Voice agents: Future AGI, which ships first-party voice and chat simulation.

Common mistakes when picking a Grafana alternative for LLMs

• Treating LLM observability as APM with prompts. Latency and error rate are necessary but not sufficient. Without eval pass-rate trend, you ship quality regressions blind. See LLM monitoring vs observability for where the line sits.
• Building LLM dashboards in Grafana from scratch. It is doable, but every new LLM panel is yours to maintain. A dedicated LLM tool ships those dashboards out of the box.
• Picking on demo dashboards. Vendor demos use clean prompts and idealized failures. Run a domain reproduction with your real traces, your model mix, and your concurrency.
• Pricing only the subscription. Real cost equals subscription plus trace volume, judge tokens, retries, storage retention, and the infra team that runs self-hosted services.
• Treating OSS and self-hostable as the same. Phoenix is source available under ELv2, not OSI open source. Langfuse has enterprise directories outside MIT. Grafana core is AGPLv3.
• Skipping the multi-tool plan. Plan for Grafana on infra plus a dedicated LLM tool. Budget for the duplication cost.

Recent LLM observability updates

Keep Grafana for infrastructure and give LLMs their own layer

If Grafana already runs your infrastructure dashboards, you do not have to rip it out to get LLM observability. traceAI is Apache-2.0 instrumentation built on OpenTelemetry, and its spans land in Grafana, Datadog, Jaeger or Future AGI, so the LLM layer sits next to the stack you already run.

• LLM-native tracing: traceAI captures LLM calls, retrieval steps, tool calls and agent decisions in Python, TypeScript, Java and C#, following the OpenTelemetry GenAI semantic conventions. Future AGI stores spans in ClickHouse.
• Span-attached evals: eval scores attach to a span or a whole trace, from custom evals or built-ins such as Groundedness, Detect Hallucination, Tool Call Accuracy and Task Completion.
• Dashboards and alerts: custom dashboards chart span count, error count, latency, token usage and eval scores by model, user or any span attribute. Alerts go to email or Slack on latency, errors, token spend or eval thresholds.
• Gateway and guardrails: the Agent Command Center is an OpenAI-compatible gateway with routing, caching, budgets and guardrail checks on the same platform.

Grafana can stay your infrastructure dashboard. Put the LLM layer in Future AGI, where traces, evals, dashboards, the gateway and guardrails share one platform, on Cloud or self-hosted with the self-hosting guide, and start free with pay-as-you-go usage. Future AGI is SOC 2 Type II, and a HIPAA BAA and SAML SSO come with paid add-ons. For the wider field, see Best LLM Monitoring Tools.

Send your first LLM traces in minutes with the Observe quickstart.

Sources

• Grafana Cloud pricing
• Grafana: Send OpenTelemetry traces to Agent Observability, no SDK required
• Datadog pricing
• Datadog Agent Observability docs
• Langfuse pricing
• Langfuse GitHub repo
• Langfuse license file
• Phoenix docs
• Phoenix GitHub repo
• Helicone pricing
• Helicone GitHub repo
• Mintlify acquires Helicone
• New Relic pricing
• Honeycomb pricing